Department

Product & Engineering

Location

Noida, India

Job scope

India

Work setting

Work from office (WFO)

About Doceree : Doceree is the world's only AI-powered Operating System for healthcare marketing. We aim to be a catalyst for change, improving healthcare by enabling more meaningful interactions with HCPs. Our patented AI brings deeper context to every HCP touchpoint-understanding who HCPs are, what they're exploring, how they engage, and when they make decisions, all in a privacy-compliant way. With this enriched context, every message becomes clearer, more relevant, and more likely to drive better healthcare outcomes. In our journey of 5 years, we have earned four patents for innovation and even won a Silver award at the Cannes Lions, one of the world's top advertising honors. Over the years, we've also had the opportunity to work with 115+ pharma companies and collaborate with 30+ media publications, 150+ EHR platforms, 2,000+ publisher networks, and 35+ hospitals and health systems. Our ecosystem connects us with more than 6 million verified doctors worldwide. Today, Doceree operates across 25+ countries, with teams based in Current Jersey, London, and India.

Technology can connect the fragmented healthcare ecosystem to deliver information when it is most needed to improve patients' outcomes. We are expanding our footprints across the globe and enhancing our services, offering, and developing new products and solutions to address the unmet needs of industry.

Purpose of the Job : Doceree is building the first proactive intelligence layer for pharma brand teams - an agentic AI system that turns clinical intent signals, campaign data, and market context into a daily brief that drives a decision in under five minutes. We are hiring AI Engineers to build the systems behind that surface.





You will design and ship production AI systems - LLM-powered pipelines, agentic workflows, retrieval over heterogeneous healthcare data, evaluation harnesses, and the orchestration layer that sits between our signal foundation and the brand manager's morning brief. You'll work closely with data scientists, product, and platform engineering to take prototypes from a notebook to something a brand team relies on everyday.

You'll thrive here if you enjoy living at the seam between LLMs, traditional ML, and well-engineered backend systems - and if you care about making AI useful, reliable, and measurably better in a regulated, real-world domain.

Key Responsibilities :

- Design, build, and ship production-grade LLM and agentic AI systems powering anomaly detection, contextual synthesis, next-best-action recommendations, and one-click activation across the Daily Command product surface
- Build robust retrieval-augmented generation (RAG) pipelines over Doceree's clinical intent signals, campaign data, market data, and partner data - including chunking, embedding, indexing, hybrid retrieval, reranking, and grounding strategies
- Implement agent orchestration patterns (tool use, planning, multi-step reasoning, structured outputs, guardrails) using modern frameworks (e.g., LangGraph, LlamaIndex, custom orchestration) and own the latency, cost, and reliability of those agents end-to-end




- Build evaluation and observability for AI features - offline eval sets, golden datasets, LLM-as-judge harnesses, regression tests, online metrics, prompt/version tracking, and trace inspection
- Engineer prompts, system instructions, and tool interfaces as first-class artifacts - versioned, tested, and tied to measurable business outcomes (lift, NBRx correlation, decision time, action acceptance rate)
- Integrate and benchmark multiple model providers (OpenAI, Anthropic, Google, open-source via vLLM/TGI), and make pragmatic build-vs-buy and model-routing decisions based on quality, latency, and unit economics
- Partner with data scientists to productionize ML models (classification, ranking, recommendation, embedding, forecasting) - wrapping them in services, pipelines, and APIs that downstream agents and product surfaces can consume
- Own scalable, cloud-native deployment of AI services on AWS, with strong MLOps/LLMOps hygiene: CI/CD for models and prompts, feature/vector stores, monitoring, drift detection, cost guardrails, and safe rollout
- Implement safety, privacy, and compliance controls appropriate for healthcare/HCP data - PII/PHI handling, prompt injection defenses, output validation, auditability, and human-in-the-loop where it matters
- Collaborate with product and design to translate fuzzy user problems into well-scoped AI subsystems, then prototype quickly, evaluate honestly, and harden the winner
- Stay current with advances in LLMs, agents, retrieval, evaluation, and inference infrastructure, and bring back what's genuinely useful

Qualifications - Experience, Skills & Education :

- B.Tech / M.Tech / Ph.D. in Computer Science, Information Technology, Statistics, or related quantitative discipline from a Tier

📌 Ai Engineer / Senior Engineer (Noida)
🏢 Doceree
📍 Noida