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; ElevenLabs / Smallest.ai TTS; LlamaParse / JinaAI / Mistral OCR.Observability & Monitoring (nice- to- have).OpenTelemetry | Prometheus | LangSmith | Pydantic Logfire .Cloud & DevOps (nice- to- have).(ref : hirist.tech)