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The job description asks for Python, LLM Engineering, Retrieval and Search, Evaluation and Observability, Unstructured Data Processing, Full-Stack Development, Cloud and DevOps and Security and Responsible AI. Make sure your resume shows the ones you have, in the words the job uses: applicant tracking systems look for them.

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This is based in Gurgaon, Haryana.

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Senior AI Engineer

Panamoure

Gurgaon, Haryana, India

Job Description: Senior Applied AI Engineer

Experience: 5+ Years

Employment Type: Full-Time

Location: Gurugram

Working Days: Monday to Friday

About Panamoure

Panamoure Group LLP is a UK-based business transformation consultancy specialising in private equity-backed portfolio companies. Our India Delivery Centre in Gurugram serves as the engineering and automation backbone for global operations, delivering intelligent process automation, AI-driven workflows, data engineering, Power Platform solutions, and digital transformation initiatives.

Role Overview

We are looking for a Senior Applied AI Engineer to design, build and run AI-powered solutions for our clients, from early proof of concept to production. You will work across the full stack: data, models, application logic and the interfaces people use, with a focus on solutions that are reliable, secure and measurably useful.

Responsibilities

Design, build and deploy solutions using large language models, taking them from proof of concept to production.
Build pipelines that process unstructured and structured data, such as documents, transcripts, emails and databases, and turn it into reliable, structured output.
Develop retrieval and search solutions, choosing the right approach for each problem.
Build agentic workflows and tool-using AI systems where they add real value.
Create evaluation frameworks and monitoring that track output quality, cost and latency in production.
Build user-facing applications, APIs and dashboards that put AI output in front of users.
Turn prototypes and proofs of concept into maintainable, production-grade systems.
Set and uphold engineering standards for version control, testing, deployment, monitoring and documentation.
Make sure solutions meet security, privacy and responsible AI requirements, including data protection, access control, defence against prompt injection and appropriate human oversight.
Assess new models, tools and techniques, and advise on feasibility, model selection and build-versus-buy decisions.
Work with business and client stakeholders to turn problems into practical technical solutions.

Must-Have Technical Skills

Python: Production-level Python, with strong software engineering fundamentals: system design, testing and code quality.
LLM Engineering: Experience with commercial and open-source models, such as Anthropic, OpenAI and Azure OpenAI, including prompt design, structured outputs, tool use, and managing cost, latency and failures.
Retrieval and Search: Embeddings, vector databases, chunking and hybrid search.
Evaluation and Observability: Test sets, automated quality checks and production monitoring of AI systems.
Unstructured Data Processing: Document parsing, OCR and working with transcripts.
Full-Stack Development: TypeScript and React or an equivalent framework, plus API design.
Cloud and DevOps: At least one major cloud platform, CI/CD, containers, and secrets and environment management.
Security and Responsible AI: Data protection, access control and AI-specific risks such as prompt injection.

Nice-to-Have

Agent Frameworks: Frameworks and protocols such as LangGraph or the Model Context Protocol (MCP).
Open-Source Models: Fine-tuning and hosting open-source models.
Classical ML and NLP: Techniques such as classification and entity extraction.
Data Engineering: SQL, data modelling and pipeline orchestration.
Microsoft Ecosystem: Azure AI services, Microsoft 365 integration and Power Platform.
Speech and Vision: Experience with speech or vision models.
Client Exposure: Consulting or client-facing experience.

What This Role Is Not

This is not a data science or machine learning research role. We are not looking for people whose main experience is building statistical models or training models from scratch.

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