Executive- AI Engineering

Job Title:

About the Role:

Senior AI Engineer GenAI & Applied ML

You’ll work hands-on across the full AI stack — from fine-tuning models and writing APIs to implementing text-to-SQL and voice-enabled assistants. If you have a strong track record of single-handedly delivering complex AI systems and a deep understanding of modern ML and GenAI trends.

Key Responsibilities:

Design, build, and deploy production-ready AI solutions

• Develop intelligent

  chat agents, voice-enabled bots, and autonomous agentic AI systems

  tailored to various domains and user contexts.
• Implement

  context-aware systems using RAG

  (Retrieval-Augmented Generation), custom embeddings, and vector databases to optimize relevance and response quality.

• Fine-tune and customize

  open-source and proprietary LLMs (e.g., GPT, Claude, LLaMA, Mistral, Phi 4) for domain-specific applications and enhanced performance.
• Build and expose scalable APIs to serve AI models and integrate them into broader application ecosystems.
• Own the

  full AI lifecycle

  — from architecture and experimentation to deployment and performance tuning.
• Translate business needs into technical blueprints in collaboration with product owners, data teams, and domain experts.
• Proactively research and prototype with the latest advancements in GenAI, agent frameworks, and multimodal models to drive innovation.
• Understanding of

  evaluation frameworks

  for GenAI systems, including prompt robustness, hallucination mitigation, and human-in-the-loop feedback loops.

Requirements:

• 4

  + years

  of hands-on experience in building and deploying AI/ML/NLP applications, including at least

  2 years working with LLMs or GenAI systems

  in production environments.
• Proven experience with

  state-of-the-art LLMs/SLMs

  , such as GPT-3.5/4, Claude, LLaMA, Mistral, or similar, including prompt engineering, model evaluation, and fine-tuning.
• Practical expertise in building

  RAG pipelines

  , designing

  embedding workflows

  , and using

  vector databases

  like FAISS, Pinecone, or Weaviate.
• Strong Python programming skills with experience in

  Hugging Face Transformers

  ,

  LangChain

  ,

  LanGraph,

  OpenAI/Anthropic SDKs

  , and other GenAI frameworks.
• Solid grasp of ML/NLP fundamentals including

  data preprocessing

  ,

  model optimization

  ,

  evaluation metrics

  , and

  real-world deployment strategies

  .
• Familiarity with deploying AI models through APIs, cloud platforms, or containerized environments (e.g., Docker, FastAPI, Flask).
• Excellent analytical and debugging skills; ability to independently research, prototype, and solve complex problems end-to-end.
• Bonus: Exposure to

  voice AI systems

  , speech-to-text APIs, or audio-driven interfaces is an advantage.

Nice to Have:

• Familiarity with

  regulatory and compliance frameworks

  relevant to AI in life sciences, such as

  GxP

  ,

  HIPAA

  ,

  GDPR

  , or similar standards.
• Experience integrating AI models into

  enterprise platforms

  ,

  pharma-specific systems

  , or

  regulated IT environments

  .
• Knowledge of

  agent frameworks

  (e.g., AutoGen, CrewAI, LangGraph) and how to operationalize them in real-world use cases.
• Exposure to

  speech recognition APIs

  , voice interface design, or building

  voice-enabled assistants

  .

Educational Qualifications:

• Bachelor’s Degree

  in Engineering (B.E./

  B.Tech.

  ) or

  Master’s Degree in Computer Applications (MCA/ M.Tech)

  .

• Additional Qualifications

  in

  Artificial Intelligence, Machine Learning, or Data Science

  are highly desirable.

Benefits We Offer:

• Access to a

  state-of-the-art facility

  equipped with modern and collaborative workspaces.

• Free gym facility

  to promote health and well-being of employees.
• Dynamic and inclusive work environment focused on innovation and continuous learning.
• Opportunity to work on impactful projects at the intersection of AI and life sciences.
• Competitive compensation.