About Brillio: Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction. Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work certification year after year. Lead Engineer Primary Skills AngularJS, JavaScript, CSS3, React JS, CI/CD Pipeline, Java, Hibernate, Oracle RDBMS, Kafka, Docker, Spring Core, Spring Boot, HTML5, Kubernetes, MySQL Specialization Java Fullstack with Microservices: Software Development Lead Job requirements Role: Full Stack Developer (React, GoLang, Python, Java, Node.js, AWS) Employment Type: Permanent W2 or Full Time Location: Boston, MA Must have Skills Frontend: - ReactJS Backend: - (Golang, Python, Java, Node.js) any 2-stack needed Cloud:- AWS Job Summary We are looking for a highly skilled Senior Full Stack Engineer to design, build, and scale customer-facing technology platforms. This role requires strong hands-on expertise across frontend and backend engineering, with the ability to deliver end-to-end solutions using modern web technologies, cloud-native services, APIs, microservices, and distributed systems. The ideal candidate brings strong engineering fundamentals, a product mindset, and the ability to independently solve complex technical problems in a collaborative, fast-paced environment. Key Responsibilities Design, build, and maintain scalable full-stack applications end to end - from frontend UI to backend services, APIs, and databases - using React, TypeScript, Go, Java, Python, and Node.js. Build and enhance RESTful APIs, gRPC/Thrift integrations, microservices, and distributed systems supporting business-critical workflows. Participate in architecture reviews, technical design discussions, and code reviews; drive engineering practices across coding standards, automated testing (incl. Cypress UI regression), security, observability, and CI/CD. Troubleshoot complex production issues and drive improvements to reliability, performance, and user experience. Contribute to cloud infrastructure and deployment automation across AWS-based environments. Mentor junior and mid-level engineers, and collaborate closely with product managers, architects, and designers to deliver high-quality software. Communicate technical decisions, risks, and trade-offs clearly to stakeholders and team members. Required Skills & Experience Technical Experience Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience, with 5+ years of hands-on, production-grade full-stack experience. Strong frontend (ReactJS, TypeScript, JavaScript, hooks, reusable UI components) and backend (Go, Java, Python, or Node.js) development building APIs, services, and integrations (REST, gRPC, Thrift; Koa). Solid understanding of system design, distributed systems, scalability, and performance optimization. Working knowledge of relational (PostgreSQL, MySQL, Aurora, RDS) and non-relational (MongoDB, DocumentDB, DynamoDB, Redis) databases. Hands-on AWS experience (ECS, Lambda, API Gateway, S3, CloudWatch, and similar services). Experience with Docker, CI/CD (CircleCI), Terraform, and modern DevOps practices. Experience writing unit, integration, and UI tests (Jest, Cypress, or similar). Agile/Scrum delivery experience with strong ownership across distributed, cross-time-zone teams. Familiarity with AI-assisted engineering tools (Gemini, Claude Code, GitHub Copilot) to boost productivity and code quality. Professional Skills Proven ability to independently own and deliver complex technical initiatives. Experience collaborating effectively within distributed and agile teams. Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities. Experience mentoring engineers and driving technical excellence across teams. Nice to Have Skills Experience with Elasticsearch for search, analytics, and large-scale data retrieval. Knowledge of Thrift or similar RPC frameworks for service-to-service communication. Experience working within monorepo environments and large-scale frontend codebases. Familiarity with Bazel build systems. Infrastructure-as-Code experience using Terraform, AWS CDK, or CloudFormation. Experience contributing to shared UI component libraries and enterprise design systems. Exposure to event-driven architectures and messaging technologies such as Kafka or AWS EventBridge. Experience in real estate technology, marketplace platforms, or customer-facing SaaS products. $120,000 - $130,000 a year Know more about Brillio : PPE: Equal Employment Opportunity Declaration Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation. Know what it's like to work and grow at Brillio: Click here
09/25/2026
Full time
About Brillio: Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction. Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work certification year after year. Lead Engineer Primary Skills AngularJS, JavaScript, CSS3, React JS, CI/CD Pipeline, Java, Hibernate, Oracle RDBMS, Kafka, Docker, Spring Core, Spring Boot, HTML5, Kubernetes, MySQL Specialization Java Fullstack with Microservices: Software Development Lead Job requirements Role: Full Stack Developer (React, GoLang, Python, Java, Node.js, AWS) Employment Type: Permanent W2 or Full Time Location: Boston, MA Must have Skills Frontend: - ReactJS Backend: - (Golang, Python, Java, Node.js) any 2-stack needed Cloud:- AWS Job Summary We are looking for a highly skilled Senior Full Stack Engineer to design, build, and scale customer-facing technology platforms. This role requires strong hands-on expertise across frontend and backend engineering, with the ability to deliver end-to-end solutions using modern web technologies, cloud-native services, APIs, microservices, and distributed systems. The ideal candidate brings strong engineering fundamentals, a product mindset, and the ability to independently solve complex technical problems in a collaborative, fast-paced environment. Key Responsibilities Design, build, and maintain scalable full-stack applications end to end - from frontend UI to backend services, APIs, and databases - using React, TypeScript, Go, Java, Python, and Node.js. Build and enhance RESTful APIs, gRPC/Thrift integrations, microservices, and distributed systems supporting business-critical workflows. Participate in architecture reviews, technical design discussions, and code reviews; drive engineering practices across coding standards, automated testing (incl. Cypress UI regression), security, observability, and CI/CD. Troubleshoot complex production issues and drive improvements to reliability, performance, and user experience. Contribute to cloud infrastructure and deployment automation across AWS-based environments. Mentor junior and mid-level engineers, and collaborate closely with product managers, architects, and designers to deliver high-quality software. Communicate technical decisions, risks, and trade-offs clearly to stakeholders and team members. Required Skills & Experience Technical Experience Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience, with 5+ years of hands-on, production-grade full-stack experience. Strong frontend (ReactJS, TypeScript, JavaScript, hooks, reusable UI components) and backend (Go, Java, Python, or Node.js) development building APIs, services, and integrations (REST, gRPC, Thrift; Koa). Solid understanding of system design, distributed systems, scalability, and performance optimization. Working knowledge of relational (PostgreSQL, MySQL, Aurora, RDS) and non-relational (MongoDB, DocumentDB, DynamoDB, Redis) databases. Hands-on AWS experience (ECS, Lambda, API Gateway, S3, CloudWatch, and similar services). Experience with Docker, CI/CD (CircleCI), Terraform, and modern DevOps practices. Experience writing unit, integration, and UI tests (Jest, Cypress, or similar). Agile/Scrum delivery experience with strong ownership across distributed, cross-time-zone teams. Familiarity with AI-assisted engineering tools (Gemini, Claude Code, GitHub Copilot) to boost productivity and code quality. Professional Skills Proven ability to independently own and deliver complex technical initiatives. Experience collaborating effectively within distributed and agile teams. Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities. Experience mentoring engineers and driving technical excellence across teams. Nice to Have Skills Experience with Elasticsearch for search, analytics, and large-scale data retrieval. Knowledge of Thrift or similar RPC frameworks for service-to-service communication. Experience working within monorepo environments and large-scale frontend codebases. Familiarity with Bazel build systems. Infrastructure-as-Code experience using Terraform, AWS CDK, or CloudFormation. Experience contributing to shared UI component libraries and enterprise design systems. Exposure to event-driven architectures and messaging technologies such as Kafka or AWS EventBridge. Experience in real estate technology, marketplace platforms, or customer-facing SaaS products. $120,000 - $130,000 a year Know more about Brillio : PPE: Equal Employment Opportunity Declaration Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation. Know what it's like to work and grow at Brillio: Click here
About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description Shape the Future of Enterprise AI at Scale We are looking for a seasoned Software Architect (Sr. Consultant title at Visa) to join our Corporate Generative AI Technologies team. In this role, you will help architect, build, and scale enterprise-grade Generative AI and agentic applications. This is a senior, hands-on engineering role for someone who brings strong system design judgment, full-stack product engineering depth, and the ability to translate complex business workflows into scalable, reliable AI-enabled automation solutions. You will work on platforms and applications that use AI-native application patterns, including large language models, agentic workflows, retrieval-augmented generation, tool orchestration, API integrations, ETL pipelines, and data systems to transform business processes into intelligent, reliable, and scalable workflows. You will help solve hard engineering problems such as decomposing complex workflows into reusable agents, designing secure human-in-the-loop systems, and building production-grade GenAI applications that can be monitored, evaluated, governed, and continuously improved. As a Senior Consultant (Staff Software Architect), you will operate with a high degree of autonomy, ownership, and technical judgment while collaborating closely with your manager and the broader engineering team to align on technical direction. You will be responsible for building high-quality software while also influencing system design decisions, architectural direction, engineering standards, and best practices across the team. Key Responsibilities Design, build, and scale enterprise-grade GenAI and agentic applications, with a strong focus on maintainable, secure, scalable, reliable, and production-ready architecture. Own architecture and delivery of major GenAI subsystems; lead design reviews; mentor I4/I5 engineers; define reusable patterns and production standards. Apply strong system design judgment to build full-stack, production-grade applications with robust API design, workflow orchestration, secure data flows, observability, and operational readiness. Build modern frontend experiences using React and established frontend patterns, including component-based architecture, state management, reusable UI components, accessibility, performance optimization, and seamless integration with backend APIs and AI-enabled services. Design and implement scalable backend services using Python, Node.js, and/or Java, including secure APIs, asynchronous processing, background jobs, authentication, authorization, logging, error handling, and system resiliency. Work with databases like PostgreSQL, Redis, vector databases, and related technologies, including schema design, indexing strategies, query optimization, transaction management, caching patterns, migrations, and data access patterns. Implement backend capabilities for AI-enabled and agentic workflow automation, including intent routing, agent orchestration, tool execution, API integrations, data retrieval, multi-step execution, workflow state management, human approval flows, guardrails, auditability, and enterprise system integration. Develop AI-native capabilities using OpenAI, Anthropic, and related LLM APIs/SDKs, including prompt orchestration, tool/function calling, structured outputs, streaming responses, model routing, and evaluation patterns. Apply deep knowledge of modern LLM capabilities to make informed engineering decisions around model selection, context management, latency, cost, reliability, output quality, safety, and user experience. Design and implement retrieval-augmented generation solutions, including ingestion pipelines, ETL workflows, embeddings, vector database integration, retrieval strategies, relevance ranking, grounding, and retrieval quality evaluation. Build and deploy cloud-native applications using containers, DevOps practices, CI/CD pipelines, automated testing, monitoring, and operational automation. Work closely with engineering teammates and cross-functional partners to align with team priorities, translate ambiguous requirements into proof-of-concepts, then evolve them into production-quality solutions through shared ownership and hands-on collaboration. Implement observability and operational excellence for GenAI applications, including end-to-end tracing, workflow telemetry, model evaluation, and monitoring to ensure secure, reliable, and production-ready AI systems. Technical Skills: Languages & Frameworks: Python, FastAPI, LangGraph Cloud & Infrastructure: AWS, Azure, Docker, Kubernetes, ECS DevOps: Git, CI/CD pipelines Anthropic / OpenAI SDKs, MCP, A2A Databases & Storage: Pinecone, Redis, PostgreSQL Monitoring & Governance: Prometheus, Grafana, audit logging, access control Frontend: ReactJS, HTML, CSS, JavaScript Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 8+ years of relevant work experience with a Bachelor's Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience. At least 8 years of experience designing, building, and operating complex distributed software systems in production environments. Strong background in software architecture, distributed systems, API design, cloud-native platforms, and data-intensive applications. Experience with cloud platforms, containerized environments, CI/CD systems, and observability tooling. Hands-on experience with React and backend development using Python, Node.js, Java, or similar languages. Strong communication skills with the ability to translate complex technical concepts to business stakeholders Preferred Qualifications: 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD Experience building AI-enabled, data-driven, workflow automation, search, conversational, or machine learning-powered applications is highly valued. Direct experience with Generative AI technologies, LLMs, RAG architectures, or agentic systems is preferred but not required for candidates with exceptional software architecture and distributed systems experience. Experience driving technical strategy and influencing architectural direction across organizations. Expertise in system design tradeoffs involving scalability, security, reliability, performance, cost, and developer productivity. Deep understanding of modern LLM ecosystems, agent frameworks, retrieval architectures, and enterprise AI deployment patterns. Familiarity with modern AI architectures including agentic workflows, memory systems, tool orchestration, MCP, and A2A frameworks Proven ability to lead cross-functional AI initiatives, including PoC development, stakeholder alignment, and enterprise rollout. Information for US Applicants For roles located in the US, the estimated salary range for this position is $162,500.00 to $ 260,400.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
09/24/2026
Full time
About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description Shape the Future of Enterprise AI at Scale We are looking for a seasoned Software Architect (Sr. Consultant title at Visa) to join our Corporate Generative AI Technologies team. In this role, you will help architect, build, and scale enterprise-grade Generative AI and agentic applications. This is a senior, hands-on engineering role for someone who brings strong system design judgment, full-stack product engineering depth, and the ability to translate complex business workflows into scalable, reliable AI-enabled automation solutions. You will work on platforms and applications that use AI-native application patterns, including large language models, agentic workflows, retrieval-augmented generation, tool orchestration, API integrations, ETL pipelines, and data systems to transform business processes into intelligent, reliable, and scalable workflows. You will help solve hard engineering problems such as decomposing complex workflows into reusable agents, designing secure human-in-the-loop systems, and building production-grade GenAI applications that can be monitored, evaluated, governed, and continuously improved. As a Senior Consultant (Staff Software Architect), you will operate with a high degree of autonomy, ownership, and technical judgment while collaborating closely with your manager and the broader engineering team to align on technical direction. You will be responsible for building high-quality software while also influencing system design decisions, architectural direction, engineering standards, and best practices across the team. Key Responsibilities Design, build, and scale enterprise-grade GenAI and agentic applications, with a strong focus on maintainable, secure, scalable, reliable, and production-ready architecture. Own architecture and delivery of major GenAI subsystems; lead design reviews; mentor I4/I5 engineers; define reusable patterns and production standards. Apply strong system design judgment to build full-stack, production-grade applications with robust API design, workflow orchestration, secure data flows, observability, and operational readiness. Build modern frontend experiences using React and established frontend patterns, including component-based architecture, state management, reusable UI components, accessibility, performance optimization, and seamless integration with backend APIs and AI-enabled services. Design and implement scalable backend services using Python, Node.js, and/or Java, including secure APIs, asynchronous processing, background jobs, authentication, authorization, logging, error handling, and system resiliency. Work with databases like PostgreSQL, Redis, vector databases, and related technologies, including schema design, indexing strategies, query optimization, transaction management, caching patterns, migrations, and data access patterns. Implement backend capabilities for AI-enabled and agentic workflow automation, including intent routing, agent orchestration, tool execution, API integrations, data retrieval, multi-step execution, workflow state management, human approval flows, guardrails, auditability, and enterprise system integration. Develop AI-native capabilities using OpenAI, Anthropic, and related LLM APIs/SDKs, including prompt orchestration, tool/function calling, structured outputs, streaming responses, model routing, and evaluation patterns. Apply deep knowledge of modern LLM capabilities to make informed engineering decisions around model selection, context management, latency, cost, reliability, output quality, safety, and user experience. Design and implement retrieval-augmented generation solutions, including ingestion pipelines, ETL workflows, embeddings, vector database integration, retrieval strategies, relevance ranking, grounding, and retrieval quality evaluation. Build and deploy cloud-native applications using containers, DevOps practices, CI/CD pipelines, automated testing, monitoring, and operational automation. Work closely with engineering teammates and cross-functional partners to align with team priorities, translate ambiguous requirements into proof-of-concepts, then evolve them into production-quality solutions through shared ownership and hands-on collaboration. Implement observability and operational excellence for GenAI applications, including end-to-end tracing, workflow telemetry, model evaluation, and monitoring to ensure secure, reliable, and production-ready AI systems. Technical Skills: Languages & Frameworks: Python, FastAPI, LangGraph Cloud & Infrastructure: AWS, Azure, Docker, Kubernetes, ECS DevOps: Git, CI/CD pipelines Anthropic / OpenAI SDKs, MCP, A2A Databases & Storage: Pinecone, Redis, PostgreSQL Monitoring & Governance: Prometheus, Grafana, audit logging, access control Frontend: ReactJS, HTML, CSS, JavaScript Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 8+ years of relevant work experience with a Bachelor's Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience. At least 8 years of experience designing, building, and operating complex distributed software systems in production environments. Strong background in software architecture, distributed systems, API design, cloud-native platforms, and data-intensive applications. Experience with cloud platforms, containerized environments, CI/CD systems, and observability tooling. Hands-on experience with React and backend development using Python, Node.js, Java, or similar languages. Strong communication skills with the ability to translate complex technical concepts to business stakeholders Preferred Qualifications: 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD Experience building AI-enabled, data-driven, workflow automation, search, conversational, or machine learning-powered applications is highly valued. Direct experience with Generative AI technologies, LLMs, RAG architectures, or agentic systems is preferred but not required for candidates with exceptional software architecture and distributed systems experience. Experience driving technical strategy and influencing architectural direction across organizations. Expertise in system design tradeoffs involving scalability, security, reliability, performance, cost, and developer productivity. Deep understanding of modern LLM ecosystems, agent frameworks, retrieval architectures, and enterprise AI deployment patterns. Familiarity with modern AI architectures including agentic workflows, memory systems, tool orchestration, MCP, and A2A frameworks Proven ability to lead cross-functional AI initiatives, including PoC development, stakeholder alignment, and enterprise rollout. Information for US Applicants For roles located in the US, the estimated salary range for this position is $162,500.00 to $ 260,400.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI C3 AI is looking for Senior Software Engineers to join the rapidly growing Data org within the Platform Engineering department. Successful candidates will get the opportunity to work on high-value technologies at the intersection of large-scale distributed systems, data infrastructure, and machine learning. You will design, develop, and maintain various features in a highly scalable and extensible AI/ML platform for large-scale applications, involving data science, distributed systems, and multi-cloud strategy. You will be given opportunities to take ownership of components, collaborate to drive technical direction, and work on interesting, impactful projects. Join us in building the next-generation AI/ML platform at petabyte level scale that powers some of the world's largest companies in Energy, Financial Services, Utilities, Health Care, Aerospace, Defense, etc. Accelerate your career in the leading enterprise AI company that is in a hyper-growth trajectory. Responsibilities: Design and develop infrastructure and services to enable data pipelines for petabyte level scale and more. Design and develop abstractions over datastores such as Cassandra, PostgreSQL, Snowflake, etc. Design and develop file system abstractions over AWS S3, Azure Blobs, HDFS, etc. Design and develop connectors to various external data stores. Design and develop distributed system components for stream processing, queueing, batch processing, analytics engines, etc. Develop and maintain industry-leading, high-performance APIs for AL/ML applications. Develop and maintain features for distributed computations over large-scale data for ML workflows. Design and develop ML-specific data-systems such as feature stores and behavioral frameworks such as recommendation engines. Design and develop integrations with distributed computing technologies such as Apache Spark, Ray, etc. for data exploration and ML workload orchestration. Design and develop integrations with data analysis libraries such as Pandas, Koalas, etc. Develop and production AI/ML models for failure prediction, data schema inferencing, etc. Work on frameworks for performance, scalability, and reliability tracking over different components of a highly extensible AI/ML platform. Work with architects, product managers, and software engineers across teams in a highly collaborative environment. Participate and provide insights in technical discussions. Write clean code following a test-driven methodology. Deliver commitments promptly following agile software development methodology. Qualifications: Bachelor of Science in Computer Science, Computer Engineering, or related fields. A minimum of 5 years of work experience in a fast-paced software company. Strong understanding of Computer Science fundamentals. High proficiency in coding with Java, C++, C#, or some other compiled language. Python would also be acceptable. Strong competency in object-oriented programming, data structures, algorithms, and software design patterns. Experience with version control systems such as Git. Experience with large-scale distributed systems. Experience with any public cloud platform (AWS, Azure, GCP). Some familiarity with distributed computing technologies (e.g., Hadoop, Spark, Kafka). Familiarity with managed versions of these technologies on public cloud platforms is also acceptable. Familiarity with technologies in the modern data science/analysis and engineering ecosystem (e.g., Pandas, Koalas). Good verbal and written technical communication ability to facilitate collaboration. Thrive in a fast-paced, dynamic environment and value end-to-end ownership of components. Intellectually curious and open to challenges. Preferred Qualifications: Advanced degree in engineering, sciences, or related field. Experience with Agile development methodology. Experience developing and working with REST and/or GraphQL APIs. Experience building scalable and reliable data pipelines. Experience with integration of data from multiple sources. Experience working with analytics and/or data processing engines. Experience developing distributed computation over large-scale data. Experience working with distributed computing frameworks (e.g., Hadoop, Spark, Kafka). Experience with data science/analysis libraries (e.g., Pandas, Koalas). Experience with task schedulers in distributed computing (e.g., Spark, Ray, Dask). Familiarity with machine learning workload orchestration in a distributed computing environment. Familiarity with workflow execution and/or optimization using DAGs, ideally for machine learning use-cases. Conceptual understanding of orchestration and resource provisioning systems (Kubernetes) C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. California Base Pay Range $145,000-$187,000 USD C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
09/24/2026
Full time
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI C3 AI is looking for Senior Software Engineers to join the rapidly growing Data org within the Platform Engineering department. Successful candidates will get the opportunity to work on high-value technologies at the intersection of large-scale distributed systems, data infrastructure, and machine learning. You will design, develop, and maintain various features in a highly scalable and extensible AI/ML platform for large-scale applications, involving data science, distributed systems, and multi-cloud strategy. You will be given opportunities to take ownership of components, collaborate to drive technical direction, and work on interesting, impactful projects. Join us in building the next-generation AI/ML platform at petabyte level scale that powers some of the world's largest companies in Energy, Financial Services, Utilities, Health Care, Aerospace, Defense, etc. Accelerate your career in the leading enterprise AI company that is in a hyper-growth trajectory. Responsibilities: Design and develop infrastructure and services to enable data pipelines for petabyte level scale and more. Design and develop abstractions over datastores such as Cassandra, PostgreSQL, Snowflake, etc. Design and develop file system abstractions over AWS S3, Azure Blobs, HDFS, etc. Design and develop connectors to various external data stores. Design and develop distributed system components for stream processing, queueing, batch processing, analytics engines, etc. Develop and maintain industry-leading, high-performance APIs for AL/ML applications. Develop and maintain features for distributed computations over large-scale data for ML workflows. Design and develop ML-specific data-systems such as feature stores and behavioral frameworks such as recommendation engines. Design and develop integrations with distributed computing technologies such as Apache Spark, Ray, etc. for data exploration and ML workload orchestration. Design and develop integrations with data analysis libraries such as Pandas, Koalas, etc. Develop and production AI/ML models for failure prediction, data schema inferencing, etc. Work on frameworks for performance, scalability, and reliability tracking over different components of a highly extensible AI/ML platform. Work with architects, product managers, and software engineers across teams in a highly collaborative environment. Participate and provide insights in technical discussions. Write clean code following a test-driven methodology. Deliver commitments promptly following agile software development methodology. Qualifications: Bachelor of Science in Computer Science, Computer Engineering, or related fields. A minimum of 5 years of work experience in a fast-paced software company. Strong understanding of Computer Science fundamentals. High proficiency in coding with Java, C++, C#, or some other compiled language. Python would also be acceptable. Strong competency in object-oriented programming, data structures, algorithms, and software design patterns. Experience with version control systems such as Git. Experience with large-scale distributed systems. Experience with any public cloud platform (AWS, Azure, GCP). Some familiarity with distributed computing technologies (e.g., Hadoop, Spark, Kafka). Familiarity with managed versions of these technologies on public cloud platforms is also acceptable. Familiarity with technologies in the modern data science/analysis and engineering ecosystem (e.g., Pandas, Koalas). Good verbal and written technical communication ability to facilitate collaboration. Thrive in a fast-paced, dynamic environment and value end-to-end ownership of components. Intellectually curious and open to challenges. Preferred Qualifications: Advanced degree in engineering, sciences, or related field. Experience with Agile development methodology. Experience developing and working with REST and/or GraphQL APIs. Experience building scalable and reliable data pipelines. Experience with integration of data from multiple sources. Experience working with analytics and/or data processing engines. Experience developing distributed computation over large-scale data. Experience working with distributed computing frameworks (e.g., Hadoop, Spark, Kafka). Experience with data science/analysis libraries (e.g., Pandas, Koalas). Experience with task schedulers in distributed computing (e.g., Spark, Ray, Dask). Familiarity with machine learning workload orchestration in a distributed computing environment. Familiarity with workflow execution and/or optimization using DAGs, ideally for machine learning use-cases. Conceptual understanding of orchestration and resource provisioning systems (Kubernetes) C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. California Base Pay Range $145,000-$187,000 USD C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.
09/23/2026
Full time
Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.
Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.
09/23/2026
Full time
Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred) Duration: 12 Months (with potential for extension) Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week. Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation Skills Required: Google Cloud Platform Experience Required: Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience). 3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos. As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking . Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask). Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows. Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services. Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build). Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost. Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices. Experience Preferred: Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale. Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases. Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data. Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents. Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements. Education Required: Bachelor's Degree Education Preferred: Master's Degree Additional Information: Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops. Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records. Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI). Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed. Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching. Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet). Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services. Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.