Role Overview:

In this role, you will design, build, and deploy Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG), and agentic workflows, integrated with enterprise data and systems. You will work alongside senior engineers to deliver reliable, scalable, and safe GenAI capabilities.

What You'll Do:

- Design and implement LLM-powered conversational experiences (chat assistants/AI Agents), integrating tools, APIs, and enterprise data sources.

- Build and maintain RAG pipelines (document ingestion, chunking, embeddings, indexing) using vector databases and AI-enabled search.

- Develop LLM inference and orchestration components (prompt templates, function/tool calling, streaming, caching) that meet defined latency and reliability targets.

- Implement safety and compliance guardrails (content filtering, prompt injection defenses, data access controls) and support red-teaming/testing of GenAI applications.

- Help optimize GenAI solutions for cost and performance (token usage, prompt compression, caching, model routing) while maintaining response quality.

- Apply Responsible AI practices for GenAI (grounding, hallucination mitigation, privacy-by-design, bias/toxicity evaluation) and align with security requirements.

- Document designs, prompts, evaluation results, and operational runbooks; contribute reusable components and code that the wider team can build on.

Qualifications:

- BE/BTech in Computer Science, Data Science, Engineering, or a related field.

- 3 - 5 years of total experience as a software engineer, including hands-on experience building and shipping AI/ML and GenAI solutions (LLMs, RAG, prompt/tool calling) using Python.

- Programming skills in Python and experience building LLM applications using common frameworks (e.g., LangChain, LangGraph).

- Hands-on experience deploying GenAI applications on cloud platforms (GCP/Azure/AWS).

- Experience with vector databases (e.g., Pinecone, Milvus, Weaviate, Elasticsearch/OpenSearch).

- Working knowledge of CI/CD, observability for GenAI systems, and Agile delivery.

Tech Stack (Good to have):

- Node, React, Terraform, Git, GitLab, Docker, Kubernetes.