Title: GEN AI Sr. Technical Lead
Area(s) of responsibility
About Birlasoft:
Birlasoft, a powerhouse where domain expertise, enterprise solutions, and digital technologies converge to redefine business processes. We take pride in our consultative and design thinking approach, driving societal progress by enabling our customers to run businesses with unmatched efficiency and innovation. As part of the CKA Birla Group, a multibillion-dollar enterprise, we boast a 12,500+ professional team committed to upholding the Group's 162-year legacy. Our core values prioritize Diversity, Equity, and Inclusion (DEI) initiatives, along with Corporate Sustainable Responsibility (CSR) activities, demonstrating our dedication to building inclusive and sustainable communities. Join us in shaping a future where technology seamlessly aligns with purpose.
About the Job – Technical Lead (GenAI Applications)
The Technical Lead will focus on the development, implementation, and engineering of GenAI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Technical Lead will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.
Key Requirements:
- 10+ years of experience in Data Science, Machine Learning, and NLP technologies.
- Strong understanding of model development, serving, and training/re-training in data-sparse environments.
- Experience with Agentic AI frameworks – LangGraph, LlamaIndex, MCP.
- Expertise in both paid (OpenAI on Azure) and open-source LLMs.
- Proficient in agent development and Python programming.
- Experience with AWS / Azure ecosystems.
- Preferably from a Pharma R&D background.
- Skilled in cloud-native application development.
- Deep knowledge of generative modeling techniques (GANs, VAEs, Transformers).
- Strong grasp of prompt engineering for instruction-based LLMs.
- Capable of designing and implementing generative models for NLP tasks.
- Collaborative mindset to work with SAs and cross-functional teams.
- Passionate about staying updated with GenAI and LLM advancements.
- Nice to have: contributions to research through publications or conferences.
- Skilled in data preprocessing and pipeline development.
- Ability to explain hallucination effects and model behavior to stakeholders.
- Experience in developing guardrails for LLMs.
- Able to deploy and optimize models for production environments.
- Nice to have: mentoring junior data scientists.
- Expertise in RDBMS, MarkLogic / NoSQL, and Elasticsearch.