Generative AI Engineer

Generative AI Engineer

About the Role

Experience: 5+ years

Tech Focus: Python, RAG, LangChain/LangGraph, OpenAI/Bedrock, SQL/Spark, Postgres/MongoDB, Pandas/scikit-learn/CV2

Cloud: AWS, GCP, Azure

We’re looking for an AI Engineer with strong Python expertise and hands-on experience delivering systems powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). You’ll design and ship resilient AI services, build robust orchestration with LangChain/LangGraph, and ensure reliability at scale with strong error handling and production failovers. The ideal candidate is a pragmatic builder who can collaborate across engineering, data, and product to ship business impact quickly and safely.

What You’ll Do

- Design & Ship LLM/RAG Services: Build Python-based services and APIs that leverage RAG pipelines (chunking, indexing, embeddings, retrieval) and LLM orchestration with LangChain/LangGraph. - Model Selection & Routing: Implement provider-agnostic strategies across OpenAI, AWS Bedrock, and other endpoints; add smart routing, fallback, and production failover patterns for high availability. - Data & Feature Pipelines: Develop ingestion, preprocessing, and transformation pipelines with Python, SQL, Spark; persist and retrieve from Postgres and MongoDB. - Document & Image Processing: Use Pandas, scikit-learn, and CV2 for unstructured data preparation (e.g., OCR-ready cleaning, page-level segmentation, image enhancements). - Reliability & Observability: Implement robust error handling, logging, metrics, tracing, and alerting; design for graceful degradation and circuit breakers. - Security & Compliance: Enforce secrets management, RBAC, data access controls, PII handling, and auditability across services. - DevEx & Reuse: Contribute to reusable libraries, templates, and documentation to accelerate delivery across teams. - Cross-Functional Delivery: Partner with data scientists, platform engineers, and product to scope requirements and ship end‑to‑end solutions.

Required Qualifications

- 5+ years of professional software engineering with a track record of independently designing and shipping complex systems. - Advanced Python with strong software engineering practices (testing, CI/CD, containerization). - Practical experience building systems with LLMs and RAG patterns (prompting, retrieval pipelines, indexing, chunking, embeddings). - Orchestration with LangChain and LangGraph for multi-step workflows. - Hands-on with OpenAI and AWS Bedrock (usage, quotas, rate limits, provider selection). - Data engineering depth with SQL, Spark, and storage systems (Postgres, MongoDB). - Proficiency with Pandas, scikit-learn, and CV2 for data preparation and feature engineering on text/images. - Strong error handling and resiliency design; proven experience implementing production failovers. - Cloud proficiency in AWS, GCP, and/or Azure; experience with infrastructure-as-code and container orchestration (e.g., Docker, Kubernetes). - Clear communication and ability to collaborate with cross-functional stakeholders.

Core Technology Stack

- Languages & Data: Python, SQL, Spark; Postgres, MongoDB - Libraries: Pandas, scikit-learn, CV2 - LLM & Orchestration: LangChain, LangGraph, RAG - Model Providers: OpenAI, AWS Bedrock (plus optional cloud-native endpoints) - Cloud: AWS, GCP, Azure - Reliability: Model selection/routing, error handling, production failovers, observability

If interested, please share your resume at: manisha.2190498@infosys.com

Location - PAN India