- Design, develop, and deploy large language model (LLM) pipelines, incorporating foundational models, retrieval-augmented generation (RAG), memory and caching mechanisms, and external API integrations.

- Implement generative AI solutions tailored to the needs of regulated industries such as financial services and healthcare.

- Apply advanced natural language processing (NLP) techniques and frameworks to address complex language understanding and generation challenges.

- Deploy, manage, and scale AI solutions on cloud platforms (AWS, Azure, GCP).

- Conduct risk assessments for GenAI pipelines, addressing :

Data privacy and security concerns
Bias and fairness in model outputs
Hallucination and factual accuracy issues
Prompt injection vulnerabilities and toxicity
Model drift and long-term performance degradation

- Develop safeguards, monitoring systems, and compliance frameworks to ensure responsible and regulatory-aligned AI deployment.

- Collaborate with cross-functional teams, including product, compliance, engineering, and data science, to deliver business-ready AI solutions.

Required Technical Skills :

- Proven expertise in developing and deploying large language models (LLMs) and generative AI solutions.

- Proficiency in Python and widely adopted AI/ML libraries, including Hugging Face Transformers, LangChain, CrewAI, Sklearn, Plotly, TRL, FastAPI

- Experience with agent development platforms and SDKs, such as :

OpenAI Agent SDK
Google Agent SDK
Dialogflow, VAPI, Salesforce AgentForce, Microsoft Copilot

Soft Skills :

- Strong problem-solving and analytical thinking abilities.

- Excellent communication skills for articulating AI concepts to diverse stakeholders.

- Ability to collaborate effectively across cross-functional teams.

- Adaptability to rapidly evolving AI technologies and industry standards.

Domain Knowledge - Healthcare is Preferred :

- Understanding of healthcare and life sciences regulatory frameworks (HIPAA, GDPR).

- Awareness of generative AI use cases in healthcare, including :

Patient engagement and virtual assistants
Medical documentation assistance
Scheduling and operational automation

Education & Experience :

- Masters degree in Computer Science, Data Science, or a related field.

- Minimum 5 years of experience in developing and deploying AI/ML solutions.

- At least 3 years of recent, hands-on experience in NLP and generative AI projects.

- Proven track record of delivering successful AI initiatives in regulated industries, preferably financial services or healthcare