Senior AI Engineer

About the job

Do you think of yourself as a modern-day artist? Read on. About the role: We’re hiring a hands-on Senior AI Engineer to build and ship practical AI features (LLM-based apps, RAG pipelines, search/embeddings, and real-time integrations). This role blends backend engineering, ML systems, and production deployment — ideal for someone who turns research ideas into reliable products. Responsibilities: • Design and implement LLM-driven features and Retrieval-Augmented Generation (RAG) pipelines. • Ingest and preprocess documents (PDFs, HTML, etc.), build embeddings, and implement vector search. • Integrate models (cloud or local) for generation and embeddings; ensure responses are grounded with source citations. • Build APIs and microservices (Node.js/Python) for inference, streaming, and real-time use cases. • Implement guardrails: prevent hallucinations, handle out-of-scope queries, and protect against prompt injection. • Deploy, monitor, and optimize AI services on cloud infra (AWS preferred): cost, latency, and autoscaling. • Collaborate with frontend engineers to integrate chat/voice interfaces (WebSockets / WebRTC). • Write clean, testable code and maintain documentation and runbooks. Required skills: • 3+ years professional experience in AI/ML engineering or backend engineering with AI products. • Practical experience with LLMs, embeddings, and RAG-style retrieval systems. • Experience with at least one vector DB or library (e.g., MongoDB Vector Search, Chroma, FAISS, Pinecone). • Strong backend skills in Node.js or Python (APIs, queues, workers). • Familiarity with deploying services on AWS (EC2/Lambda/S3); basic infra & monitoring knowledge. • Knowledge of WebSockets/SSE and basic WebRTC concepts for real-time/voice use cases. • Good software engineering practices: testing, logging, versioning, and documentation. • Clear communicator who can explain technical tradeoffs to engineers and non-engineers. Nice-to-have: • Experience with streaming LLM outputs (token-by-token), hybrid search (BM25 + embeddings), or agent/tool-calling architectures. • Background with ASR/TTS (Whisper or similar), model fine-tuning, or local LLM deployments. • Familiarity with security/privacy concerns for embeddings and user data. Benefits@Bombay DC: • Stay close to your family: You get to work 2 weeks each calendar year from the comfort of your hometown (in case you have relocated to work with us at Mumbai!) • Breathe easy with lesser travel: If you are a local resident of Mumbai and require to travel over 60 minutes (one way) to make it to the office- breathe easy! We've got you covered, once you are confirmed you can work from home every Tuesday and Thursday! • We protect your Grey Matter: We have your mental health protected, our HR team is ever present to support, listen and counsel, should you ever need help! • Winter Break- We offer a long winter break that provides an excellent opportunity to spend quality time with your near and dear ones. • We offer extended long weekends- In addition to the winter break, we also offer extended holidays designed to give you more time to unwind. • We provide caregiver leaves- We provide opportunity to take a day off at short notice or work from home on days when you are required to stay back to offer care for your parents/siblings owing to a medical emergency. • We invest in you- By subsidizing your learning initiatives, provide you some remarkable mentors to shape your professional growth and exclusive time to engage with the Founder to learn and share ideas! • We appreciate your performance- Through our Project Excellence Awards and Milestone completions when you embark upon the journey with us! Want to join the force? Apply here, or shoot an email to work@bombaydc.com

Requirements

• AI/ML engineering
• Node.js
• Python
• AWS
• WebSockets
• SSE
• WebRTC

Preferred Technologies

• AI/ML engineering
• Node.js
• Python
• AWS
• WebSockets
• SSE
• WebRTC

Benefits

• Work from hometown for 2 weeks annually
• Work from home on Tuesdays and Thursdays
• Mental health support
• Extended winter break
• Long weekends
• Caregiver leaves
• Learning initiatives