Directly builds agentic LLM workflows with LangChain/LangGraph and AWS Bedrock — clearly aligned with vibe coding and rapid AI prototyping.
About the Role
Senior Agentic AI Engineer role to design, build, and deploy multi-agent, LLM-powered workflows and production-grade AI services using Python on AWS. The primary goal is to develop scalable agentic AI applications and frameworks (planning, memory, orchestration, RAG/vector search) and lead an offshore AI sub-team.
Job Description
Role
Senior Agentic AI Engineer responsible for designing and implementing multi-agent, LLM-powered workflows and production-grade AI services using Python on AWS. The role includes architecting agent orchestration, integrating agents with enterprise systems, optimizing inference and memory, and leading an offshore AI sub-team.
Key Responsibilities
- Design and develop agentic AI workflows involving planning, reasoning, tool usage, memory, and orchestration.
- Build scalable LLM-powered applications using Python, LangChain, and LangGraph.
- Develop and integrate AI agents using AWS Bedrock and/or AWS AgentCore.
- Implement RAG pipelines, embeddings, semantic search, and vector database integrations.
- Integrate AI agents with enterprise APIs, applications, databases, and other data sources.
- Design multi-agent architectures and orchestration patterns for complex business workflows.
- Optimize prompts, agent memory, orchestration, latency, and inference performance.
- Develop reusable frameworks, components, and engineering standards for agentic AI solutions.
- Deploy, monitor, troubleshoot, and harden AI services running on AWS, ensuring security, scalability, observability, and reliability.
- Collaborate with architects, product teams, data scientists, and software engineers; lead and mentor the offshore AI sub-team and conduct technical reviews.
Requirements
- 8–12 years of experience in software engineering / AI engineering.
- Strong hands-on Python development experience.
- Proven experience building agentic AI / generative AI applications and designing multi-agent orchestration.
- Hands-on experience with LangChain and/or LangGraph.
- Strong understanding of LLMs, prompt engineering, tool calling/function calling, memory, and agent workflows.
- Hands-on experience with AWS Bedrock and/or AWS AgentCore.
- Strong experience with RAG, embeddings, semantic search, and vector databases.
- Experience integrating AI agents with enterprise APIs, databases, and external tools.
- Experience deploying and operating production-grade AI services on AWS.
- Solid software engineering fundamentals: APIs, microservices, testing, and CI/CD.
Preferred / Nice-to-Have
- Experience in Insurance / Underwriting domain.
- AWS certification.
- Experience with MLOps / LLMOps and AI observability/evaluation.
- Exposure to AWS services such as Lambda, ECS/EKS, S3, OpenSearch, DynamoDB, API Gateway, CloudWatch.
- Experience leading or mentoring AI engineering teams.
Contact
Reveille Technologies — anand.sp@reveilletechnologies.com — 8825862223