AI Solutions Architect Lead

Job Description

About the Role

We are seeking a dynamic and experienced Lead – AI Engineering to lead the design,

development, and deployment of next-generation AI solutions, with a strong focus on

Generative AI, Natural Language Processing (NLP), and Machine Learning (ML) within

the pharmaceutical industry.

As an AI Lead, you will guide a team of engineers and data scientists, drive project

execution, and collaborate closely with product and domain teams. You will be responsible

for architecting production-grade systems, mentoring technical talent, and spearheading

innovation through applied GenAI.

This role combines strategic leadership, technical depth, and hands-on execution—ideal for a

candidate passionate about operationalizing cutting-edge AI technologies for real-world

impact in life sciences.

Key Responsibilities

Lead and manage the end-to-end lifecycle of AI / GenAI projects, from scoping and

architecture to development, testing, deployment, and optimization.

Guide the development of intelligent agents, LLM-powered chatbots, and voice-

enabled systems tailored to pharmaceutical and enterprise use cases.

Architect context-aware GenAI solutions using RAG (Retrieval-Augmented

Generation), embeddings, vector databases, and multimodal models.

Oversee fine-tuning of LLMs (e.G., GPT, Claude, LLaMA, Mistral, Phi 4) and drive

responsible AI evaluation practices (e.G., hallucination mitigation, prompt

robustness).

Collaborate with cross-functional stakeholders including product owners, regulatory

teams, and business leads to align AI solutions with strategic goals.

Lead and mentor a team of AI / ML engineers and researchers, fostering technical

growth and high performance.

Stay current with emerging trends in GenAI, open-source models, agent frameworks,

• and voice tech;

translate advancements into practical applications.

Ensure projects adhere to regulatory, compliance, and data governance standards,

particularly in a GxP or HIPAA-compliant environment.

Drive innovation culture by piloting proofs-of-concept and scaling successful

initiatives across the organization.

Requirements

Minimum 6+ years of experience in AI / ML / NLP, including at least 3 years in

GenAI technologies and team leadership or technical program management.

Deep expertise in LLMs / SLMs, including prompt engineering, fine-tuning, and

building production-ready GenAI applications.

Experience with RAG pipelines, vector search (FAISS, Pinecone, Weaviate), and

embedding models.

Strong coding skills in Python and experience with frameworks like Hugging Face,

LangChain, LanGraph, OpenAI / Anthropic SDKs.

Experience with API development, MLOps, and deploying models using containers

or cloud-native tools.

Proven ability to lead cross-functional teams and translate business needs into

scalable AI systems.

Strong analytical thinking, problem-solving, and architectural design capabilities.

Nice to Have

Experience building or integrating voice assistants, speech-to-text APIs, or

multimodal GenAI interfaces.

Familiarity with agent frameworks (e.G., CrewAI, AutoGen, LangGraph) for

autonomous AI workflows.

Understanding of regulatory frameworks in life sciences (GxP, HIPAA, GDPR,

etc.).

Prior exposure to enterprise IT systems in the pharmaceutical or healthcare domain.

Educational Qualifications

Bachelor’s in Engineering (B.E. / B.Tech.) or Master’s in Computer

Applications / Technology (MCA / M.Tech.).

Certifications or specialization in AI / ML / Data Science are highly desirable.