Executive- AI Engineering

Job Description

Job Title: Executive AI Engineering Location: Andheri (Mumbai) Industry: Pharmaceutical Experience Required: 4+ years in Gen AI/ML, NLP application development About the Role: We are looking for a highly skilled Senior 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. 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.