Senior Generative AI Engineer

2 weeks ago

Chennai, India HSBC Full time

Role Overview
We're hiring a Generative AI Engineer to build, deploy, and optimize multimodal AI services across text, speech, and vision. You'll work on RAG, synthetic data generation, agent workflows, and integrate STT/TTS/OCR with scalable backend systems.

Key Responsibilities

  • Generative Pipelines: Design applications for RAG, CAG, text classification, summarization, image/video generation, OCR, and synthetic data generation.
  • Multimodal Integration: Work with STT, TTS, IVR, OCR, and vision inputs to enable seamless AI interactions.
  • AI Agent Workflows: Develop modular, multi-step orchestrations for document, conversational, and data-based user journeys.
  • Containerization & Deployment: Collaborate with DevOps to containerize services, manage Kubernetes orchestration, and implement CI/CD for agile delivery.
  • Observability: Instrument services using OpenTelemetry, Prometheus, and logging tools to ensure SLO-driven production reliability.
  • Collaboration: Work cross-functionally with product, data science, and frontend teams to define APIs (REST/GraphQL) and ensure smooth integration.
  • Documentation & Mentorship: Participate in architecture reviews, write clear documentation, and mentor junior engineers and interns.

Requirements

  • Bachelor's/Master's in Computer Science, Data Science, IT, or related field.
  • 2–3 years of experience building AI/ML products in Python.
  • Must be proficient in AI-first coding tools like Claude Code, Cursor, Roocode, etc.
  • Proven experience in deploying GenAI applications and agents in production.
  • Strong hands-on with vector search, embedding-based retrieval, STT, TTS, OCR/vision.
  • Familiarity with Docker, Kubernetes, frontend development, and CI/CD workflows.
  • Strong debugging, performance tuning, and cost-optimization skills.
  • Excellent communication, teamwork, and mentoring abilities.

Technical Stack

  • Languages & Tools (mandatory)

Python (pandas, scikit‑learn, PyTorch, Tensorflow, etc.) | Git/GitHub | AWS or GCP.

  • Generative AI stack (mandatory)
  • LangChain, LlamaIndex, transformers, frontier LLMs (OpenAI, Anthropic, Gemini models) and open models (DeepSeek, Qwen, Llama and Phi models).
  • Vector stores: FAISS, Pinecone, Qdrant, Weaviate, etc.
  • Keyword Index: Elasticsearch, Apache Solr, Typesense, etc.
  • Validation frameworks: Pydantic, Instructor, etc.
  • LLM Abstraction libraries: LiteLLM
  • Asynchronous or parallel programming: asyncio, joblib, etc.
  • API frameworks: FastAPI, Flask, etc.
  • FE prototyping: Streamlit, Gradio, etc
  • Agentic AI Frameworks (mandatory, ≥1)

Google Agents Development Kit | LangGraph | OpenAI Agents SDK | PydanticAI.

  • Speech & Vision (nice‑to‑have)

OpenAI Realtime Voice API/Whisper; TTS; LlamaParse/JinaAI/Mistral OCR.

  • Observability & Monitoring (nice‑to‑have)

OpenTelemetry | Prometheus | LangSmith | Pydantic Logfire .

  • Cloud & DevOps (nice‑to‑have)

Docker | Kubernetes | GitHub Actions.

Bonus Points

  • Domain experience in AgriTech, FinTech, HRTech or EduTech.
  • Experience and profound interest in reading and implementing research papers.
  • Open‑source contributions or published evaluation suites.
  • Exposure to managed cloud AI services (Vertex AI, Bedrock, JumpStart).
  • Familiarity with integration.

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