AI Engineer – Local AI & Internal Applications - Agra

Industry: Healthcare / Medical Devices

Location: Agra, Uttar Pradesh (On-site | Relocation required)

Experience: 1–3 Years

Compensation: Up to ₹1,50,000/month (based on experience & skills)

Employment Type: Full-Time

Notice Period: Immediate to 30 days preferred

About the Company

Our client is one of India's most established names in the medical devices and healthcare products space, with a legacy of over five decades and a strong pan-India presence. The organisation is now investing in building an AI-led internal technology ecosystem to drive efficiency, automation, and data intelligence across its operations.

This is a greenfield role — you will be among the first to build the AI function from the ground up, working closely with senior leadership.

About the Role

We are looking for a hands-on AI Engineer to build and deploy practical, privacy-first AI solutions for internal teams. You will work directly with business and management to identify use cases, prototype solutions, and ship production-ready internal tools — all within a secure, on-premise or hybrid AI environment.

Key Responsibilities

Use Case Identification

Work with business and management teams to identify and prioritise high-impact AI use cases.

Define feasibility, success metrics, and scope before development begins.

Local AI & Analytics

Build analytics solutions on structured internal data using local / on-prem LLM ecosystems.

Deliver summaries, trend reports, anomaly detection, and exception flagging — without routing sensitive data through third-party cloud APIs.

Application Development

Turn validated AI concepts into reliable, production-ready internal tools.

Own the full stack: backend, database, APIs, and a functional front-end UI.

Architecture Recommendations

Recommend deployment approaches (on-prem, hybrid, private cloud) based on data sensitivity, cost, and performance.

Document trade-offs between local and cloud AI workloads.

Multimodal AI

Work with documents, images, audio, and multimodal AI models.

Build OCR, transcription, document parsing, and extraction pipelines.

Hardware Planning

Benchmark AI models against available and prospective hardware (GPUs, edge servers, storage).

Support evaluation and procurement decisions for local AI infrastructure.

Must-Have Skills & Experience

1–3 years of hands-on AI/ML engineering experience in a production environment.

Strong Python skills and experience with at least one backend framework (FastAPI, Flask, Django, or equivalent).

Proven experience deploying open-source LLMs locally (Ollama, vLLM, LM Studio, llama.cpp, or similar).

Practical knowledge of RAG pipelines and vector databases (FAISS, Chroma, Qdrant, Weaviate).

Ability to build functional UIs for internal tools (React, Streamlit, or similar).

Experience with OCR, document parsing, or audio transcription pipelines.

Comfortable with SQL/NoSQL databases and REST API design.

Ability to work independently with non-technical business stakeholders.

Good to Have

Prior experience in healthcare, pharma, or manufacturing domain.

Knowledge of GPU server setup, CUDA, and model quantisation (GGUF, AWQ, GPTQ).

Familiarity with workflow automation tools (n8n, Airflow, LangChain, CrewAI).

Exposure to multimodal models (LLaVA, Whisper, PaddleOCR, etc.).

Experience in greenfield AI transformation projects within enterprise settings.

What We Offer

Direct access to senior leadership — your work will drive real business decisions.

Greenfield AI mandate — you shape the roadmap, not just execute it.

Stable, well-established organisation with deep domain expertise.

Opportunity to build a local AI ecosystem from scratch.