Description :

Quantanite is a global customer experience and digital solutions partner that blends cutting-edge AI with the human touch.

Headquartered in London and operating across four continents, our 2,000-strong team helps some of the worlds fastest-growing brands scale smarter, work faster, and deliver better serviceevery time.

Were not your typical outsourcing company.

We believe great service is built on two things : smart tech and even smarter people.

From our proprietary AI tools like M- BIUS to our collaborative, people-first culture, we give our teams the tools, training, and trust they need to make an impact.

If you want to be part of a forward-thinking, fast-moving, and inclusive global team that values both results and relationships, youll feel right at home here.

Position Overview :

The Senior AI Engineer reports to the Head of Technology and is responsible for the entire lifecycle of AI solutions, from design to deployment.

This includes using multi-agent workflows, advanced knowledge retrieval, and large language models to solve enterprise challenges, thereby improving business efficiency, innovation, and strategic decision-making.

The role involves leading projects such as AI Copilots, Enterprise Search Solutions, Summarization Engines, and Intelligent Automation Tools, ensuring they are robust, scalable, and production-ready.

A key aspect of the role is mentoring junior AI Engineers and maintaining high engineering standards.

This is a full-time hybrid position based in Mumbai.

Key Responsibilities :

Core Functional Responsibilities :

- Build and deploy agentic systems and multi-agent workflows using frameworks like LangChain, LlamaIndex, and OpenAI SDK.

- Develop RAG pipelines using embeddings and vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant).

- Fine-tune and optimize LLMs (GPT-4, Claude, LLaMA, Mistral, Gemini) using techniques like LoRA/QLoRA and quantization.

- Ensure solutions are secure and compliant, with guardrails, safe API usage, and PII protection.

- Implement agent monitoring and evaluation with tools like LangSmith or AgentOps to track and improve performance.

- Deliver real-world enterprise use cases such as AI copilots, workflow orchestration, and intelligent search systems.

- Mentor junior AI Engineers, reviewing their work, sharing best practices, and supporting their growth.

- Collaborate with product, data, and DevOps teams to bring AI solutions to production at scale.

- Demonstrated knowledge of agentic AI frameworks Practical experience in Small Language Model (SLM) implementation.

Required Skills & Experience :

General & Cross-Functional :

- Strong knowledge of LLMs and Gen-AI applications, with hands-on experience in fine-tuning and prompt engineering.

- Proven experience in RAG pipelines and working with vector databases.

- Practical expertise in agent frameworks (LangChain, LlamaIndex, etc.) and multi-agent orchestration.

- Ability to deploy and scale models on cloud platforms (AWS, Azure, HuggingFace, etc.)

- Proficiency in Python or similar programming languages.

- Experience with LLMOps (monitoring, evaluation, cost optimization).

- Strong track record of delivering enterprise-grade AI solutions, not just prototypes.

- Familiarity with agent monitoring/debugging tools (LangSmith, AgentOps).

- Experience mentoring or guiding junior engineers in a technical team.

- (Bonus) Experience fine-tuning open-source LLMs or contributing to community projects.

- (Bonus) Exposure to autonomous agent use cases such as research copilots or intelligent task orchestration.

Qualifications :

Essential :

Tech :

- Experience should be minimum 6 yrs to maximum 7-8yrs.

- Should have strong knowledge of Gen AI, Agentic systems and Multi Agent.

- Core attributes Communication, Leadership, Tech savvy .

Preferred :

- Industry-specific experience : BPO/KPO.

- Systems or tools experience : Gen AI, AI Agentic and Multi Agent.