Executive- AI Engineer

Job Title: Executive AI Engineering

Location: Andheri (Mumbai)

Industry: Pharmaceutical

Experience Required: 3+ years in Gen AI/ML, NLP application development

Employment Type: Full-time

About the Role

We are looking for a highly skilled AI Engineer GenAI & Applied ML to independently design, develop, and deploy advanced AI solutions. This is a senior individual contributor role focused on building production-grade Generative AI systems, agentic applications, and intelligent bots using state-of-the-art LLMs, SLMs, and embedding models.

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, we want to hear from you

Key Responsibilities

Design, build, and deploy production-ready AI solutions leveraging LLMs, SLMs, embedding models, and advanced ML techniques.

• 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.