About the Role
Job Title: Lead Generative AI Engineer (Agentic AI, RAG 2.0, Prompt Engineering, AWS)
Location: Remote / Hybrid
Job Type: Contract/Full Time
Experience: 10+ years Software Engineering/Gen AI (hands-on required)
Sponsorship is not available for this role at this time.
We are hiring a Lead Generative AI Engineer to build next-generation AI-native products using the latest advancements in LLMs, Prompt Engineering, RAG 2.0, multi-agent systems, and evaluation frameworks.
This role is ideal for engineers who have worked on real-world GenAI solutions building production-grade AI assistants, retrieval systems, autonomous agents, document intelligence pipelines, and secure AI workflows in AWS Environment.
You ll work in a fast-moving Emerging Tech environment where innovation, experimentation, and shipping production AI systems are equally valued.
Key Responsibilities
Design and build GenAI applications with Agentic AI + RAG pipelinesImplement advanced Prompt Engineering patterns:structured prompts, chain-of-thought prompting strategies, self-verification, tool promptingBuild agent orchestration workflows:tool-augmented agents, planner/executor agents, multi-agent collaborationImplement RAG 2.0 systems:hybrid retrieval (keyword + dense), reranking, chunking strategies, citations/groundingDevelop backend services using:Python microservices and GenAI pipelinesBuild document AI workflows:ingestion OCR extraction embeddings indexing retrieval response with citationsImplement LLM evaluation + observability:hallucination detection, quality scoring, groundedness checksIntegrate model safety and governance:guardrails, policy filtering, PII redaction, secure tool usageDeploy scalable solutions on cloud with CI/CD, monitoring and performance tuning
Preferred / Emerging Tech Stack (Strong Plus)
These are high priority for the Emerging Tech client:
Agentic AI / Orchestration
LangGraph, tool calling, function calling, autonomous workflowsMulti-agent collaboration patterns (planner-executor, reflection loops, memory)LLMOps & Evaluation
LangSmith, TruLens, RAGAS, DeepEval, Phoenix Arize, prompt versioningmodel behavior testing, regression testing, prompt scoringVector / Search
FAISS / Pinecone / Weaviate / Milvus / OpenSearch vector engineHybrid search + reranking (cross-encoders)Model & Training
Hugging Face, PEFT / LoRA fine-tuningPyTorch, transformersGovernance
Guardrails, prompt injection defense, PII filteringsecure retrieval systems, audit trails and citations
Required Skills
Programming & Backend
Strong experience in:Python (must-have) for Micro servives, LLM pipelines and experimentationAWS ECS and Lamda
Good to have experience in: Experience with document AI services:Java/SpringbootGenAI (Must Have)
Recent hands-on experience with:Prompt Engineering (production use)RAG pipelinesEmbeddings + vector searchhallucination mitigation + grounding/citation strategiesExperience with GenAI frameworks:LangChain / LlamaIndexLangGraph / Agent frameworksCloud & AI Platform (Must have)
Experience with one or more:AWS Bedrock / SageMakerOpenSearch vector/hybrid searchLambda / ECS / ECR
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected status.