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Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details

Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do: The Field Engineering organization at CoreWeave supports the clients running some of the largest AI workloads in the world. This team builds the tooling that engineers rely on to identify and diagnose customer issues faster. We work where AI and deterministic based systems meet live production infrastructure, so what we build has to be accurate, has to show its reasoning, and has to earn the trust of engineers who are the real experts solving issues. About the Role: As an AI Engineer, you'll design, build, and operate systems that engineers use during real customer incidents. You will define the right balance between deterministic and AI systems, and work with both. For AI systems, you'll own the agent logic, the retrieval behind it, the safeguards that stop it from acting on bad information, and the measurement that tells us whether it's actually helping. This is a full-ownership role: you ship your own services and stay responsible for how they behave in production. You'll work closely with the engineers who use what you build. In this role, you will: - Design and build AI agents that investigate and act on real customer issues. - Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop. - Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems. - Determine the optimal balance between AI and deterministic logic. - Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next. - Deploy and operate your own services on Kubernetes, including supporting them when something breaks. - Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way. Who You Are: - 3+ years of professional software engineering experience, with strong proficiency in Go or Python. - Experience taking an AI application from prototype to production use and supporting it afterward. - Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output. - Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data. - Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails. - Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom. - Experience with observability for LLM applications, including tracing, cost, and latency. - Working knowledge of Kubernetes and experience deploying services through CI/CD. - Experience integrating with third party APIs, including authentication and secrets handling. Preferred: - Experience building conversational or chat-based interfaces for internal users. - A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system. - Experience testing both deterministic and non-deterministic systems. - Experience with fine-tuning or building training datasets from production data. - Open source contributions to AI tooling or agent frameworks. Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. - You can tell the difference between the thing that's interesting and the thing that's urgent, and you'll say so out loud when they aren't the same. - You've worked with a team that already had tooling they liked, and found the integration instead of arguing for a rewrite. - You'd rather sit in on a real incident than infer how the work goes from a ticket. - Blunt feedback from the engineers using your software is the most useful thing you'll hear all week, and you don't get defensive about it. The base salary range for this role is $143,00 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Job Description We build AI agents that actually work in enterprise environments - not prototypes, not demos. We need engineer's who can own the entire agent stack: a production frontend, a robust backend, a properly secured API and identity layer, a memory architecture that scales, and LLM integrations that are model-agnostic and built to last. You'll be deployed on client engagements as the lead technical architect and builder of agentic systems running in AWS, OCI, and Azure. You'll work directly with client stakeholders, translate complex requirements into working systems, and leave behind infrastructure clients can operate and extend. You'll also help Trilagen productize our delivery approach as we scale the practice. If you've only ever built agents that run on your laptop, this isn't the role. If you've shipped agentic systems into production cloud environments and know exactly what breaks and why - we want to talk. What you'll own Full-stack agent development You design and build the entire application - not just the AI layer. This means a React or Next.js frontend with streaming, real-time agent UX; a Python or Node.js backend that orchestrates agent logic, manages state, and exposes clean APIs; and containerized, cloud-deployed services that operations teams can actually run. You own the repo, the CI/CD pipeline, the deployment, and the runbook. Multi-cloud deployment Production agent systems on all three major clouds: AWS (Lambda, ECS/Fargate, Bedrock, API Gateway), Oracle OCI (OKE, Functions, AI Services), and Azure (AKS, Azure OpenAI Service, Azure Functions). You understand the tradeoffs between platforms and can advise clients on where to run what and why. LLM integration and model strategy You have deep, hands-on experience with the leading LLM providers and their APIs - Anthropic Claude (Messages API, tool use, streaming, context management), OpenAI (GPT-4o, Assistants API, function calling), and Google Gemini (Gemini Pro/Flash, Vertex AI). You architect model-agnostic integration layers so clients aren't locked in, and you know how to select, swap, and benchmark models for specific agent tasks. Agentic architecture You understand how to design systems that do real multi-step work: tool use and function calling patterns, ReAct and plan-and-execute loops, agent-to-agent orchestration and handoffs, human-in-the-loop checkpoints, retry and failure recovery strategies, and cost/latency optimization across long-running agent workflows. Frameworks like LangGraph, CrewAI, AutoGen, and the Model Context Protocol (MCP) are tools in your toolbox, not the ceiling of your knowledge. Memory and context layer You've designed and implemented memory architectures for production agents: short-term conversational context, long-term persistent memory, RAG pipelines with vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and identity layer This is non-negotiable for our client base. You build the security envelope around every agent system you ship: OAuth 2.0 / OIDC authentication flows, API key lifecycle management, role-based access control enforced within agent workflows, secrets management (AWS Secrets Manager, Azure Key Vault, OCI Vault), audit logging for agent actions, prompt injection defense, and data residency controls. Familiarity with Okta or SailPoint ISC is a direct advantage on our engagements. Requirements 4+ years of software engineering experience with at least 2 years building and shipping LLM-powered or agentic applications in production cloud environments Hands-on depth with at least two of the three major LLM providers: Anthropic Claude, OpenAI, and Google Gemini - at the API level, not just via wrappers Full-stack proficiency: Python (FastAPI, Flask, or similar) backend, React or Next.js frontend, REST and WebSocket API design Production experience on at least two of: AWS, Azure, OCI - with real deployments, not sandbox accounts Demonstrated ability to design and implement agent memory and retrieval systems using vector databases and RAG Strong command of AI security practices: auth, RBAC, secrets management, audit logging, and prompt-level safeguards Consulting DNA - you can run a discovery session, write a technical design doc, manage client expectations, and own delivery end to end Nice to have Experience with all three LLM providers (Anthropic, OpenAI, Gemini) and model-agnostic orchestration patterns Okta and/or SailPoint ISC integration experience Cloud certifications: AWS Solutions Architect, Azure Solutions Architect, OCI Architect Benefits Benefits: 401K Health Insurance Dental Insurance Paid Time Off Paid Sick Leave

Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do: The Field Engineering organization at CoreWeave supports the clients running some of the largest AI workloads in the world. This team builds the tooling that engineers rely on to identify and diagnose customer issues faster. We work where AI and deterministic based systems meet live production infrastructure, so what we build has to be accurate, has to show its reasoning, and has to earn the trust of engineers who are the real experts solving issues. About the Role: As an AI Engineer, you'll design, build, and operate systems that engineers use during real customer incidents. You will define the right balance between deterministic and AI systems, and work with both. For AI systems, you'll own the agent logic, the retrieval behind it, the safeguards that stop it from acting on bad information, and the measurement that tells us whether it's actually helping. This is a full-ownership role: you ship your own services and stay responsible for how they behave in production. You'll work closely with the engineers who use what you build. In this role, you will: - Design and build AI agents that investigate and act on real customer issues. - Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop. - Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems. - Determine the optimal balance between AI and deterministic logic. - Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next. - Deploy and operate your own services on Kubernetes, including supporting them when something breaks. - Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way. Who You Are: - 3+ years of professional software engineering experience, with strong proficiency in Go or Python. - Experience taking an AI application from prototype to production use and supporting it afterward. - Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output. - Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data. - Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails. - Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom. - Experience with observability for LLM applications, including tracing, cost, and latency. - Working knowledge of Kubernetes and experience deploying services through CI/CD. - Experience integrating with third party APIs, including authentication and secrets handling. Preferred: - Experience building conversational or chat-based interfaces for internal users. - A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system. - Experience testing both deterministic and non-deterministic systems. - Experience with fine-tuning or building training datasets from production data. - Open source contributions to AI tooling or agent frameworks. Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. - You can tell the difference between the thing that's interesting and the thing that's urgent, and you'll say so out loud when they aren't the same. - You've worked with a team that already had tooling they liked, and found the integration instead of arguing for a rewrite. - You'd rather sit in on a real incident than infer how the work goes from a ticket. - Blunt feedback from the engineers using your software is the most useful thing you'll hear all week, and you don't get defensive about it. The base salary range for this role is $143,00 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

Job Description Job Description At ChatBotz.ai, we are seeking a highly skilled and motivated Tech Lead to join our innovative team. As a Tech Lead - Conversational AI, you will play a crucial role in developing and implementing intelligent chatbot solutions that revolutionize businesses. Responsibilities: Lead the development and implementation of conversational AI solutions using cutting-edge technologies. Collaborate with cross-functional teams to gather requirements and define project goals. Design, develop, test, and deploy highly scalable and reliable chatbot solutions. Ensure the quality, performance, and security of the chatbot applications. Stay updated with the latest advancements in conversational AI technologies and integrate them into our solutions. Provide technical guidance and mentorship to the development team. Conduct code reviews and ensure adherence to coding best practices and standards. Troubleshoot and resolve technical issues related to chatbot applications. Collaborate with stakeholders to define project timelines, deliverables, and milestones. Stay up-to-date with industry trends and emerging technologies related to conversational AI. Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Tech Lead or similar role in developing conversational AI solutions. Strong programming skills in languages such as Python, Java, or JavaScript. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. Experience with popular conversational AI platforms and frameworks such as Dialogflow, RASA, or Microsoft Bot Framework. Proficiency in working with cloud platforms like AWS, Azure, or Google Cloud Platform. Familiarity with chatbot development tools and libraries. Strong problem-solving skills and ability to think creatively. Excellent communication and leadership abilities. Join our dynamic team at ChatBotz.ai and be part of revolutionizing businesses through intelligent chatbot solutions. Apply now and contribute to creating personalized and interactive experiences for users while streamlining customer support, enhancing sales processes, and delivering exceptional 24/7 customer service.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details

AI Engineer 3 (AI Foundations) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring measurable performance and safety metrics Implement scalable pipelines for training, fine-tuning and deploying foundation or domain-specific models across multiple environments Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies Contribute to governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience contributing to development of components of AI systems with tradeoff decisions around cost, latency, throughput and accuracy 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics (accuracy, coherence, latency, cost) Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $161,800 - $184,600 for AI Engineer 3 McLean, VA: $161,800 - $184,600 for AI Engineer 3 New York, NY: $176,500 - $201,400 for AI Engineer 3 San Jose, CA: $176,500 - $201,400 for AI Engineer 3 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details

AI Engineer 3 (AI Foundations) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring measurable performance and safety metrics Implement scalable pipelines for training, fine-tuning and deploying foundation or domain-specific models across multiple environments Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies Contribute to governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience contributing to development of components of AI systems with tradeoff decisions around cost, latency, throughput and accuracy 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics (accuracy, coherence, latency, cost) Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $161,800 - $184,600 for AI Engineer 3 McLean, VA: $161,800 - $184,600 for AI Engineer 3 New York, NY: $176,500 - $201,400 for AI Engineer 3 San Jose, CA: $176,500 - $201,400 for AI Engineer 3 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details