Chennai, Tamil Nadu, India
Information Technology
Full-Time
HSBC
Overview
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
Bonus Points
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.
- 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.
- Languages & Tools (mandatory)
- 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)
- Speech & Vision (nice‑to‑have)
- Observability & Monitoring (nice‑to‑have)
- Cloud & DevOps (nice‑to‑have)
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 React/Next.js integration.
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