As an Agentic AI Lead / Architect, you will spearhead the design and deployment of autonomous, goal-oriented AI systems that transcend traditional conversational interfaces. You will operate at the intersection of cutting-edge research and enterprise-scale engineering, collaborating closely with product managers, data scientists, and executive stakeholders to translate complex business challenges into sophisticated Agentic AI architectures. Your work will directly influence the efficiency and intelligence of our digital ecosystems, enabling systems to reason, plan, and execute multi-step tasks independently, thereby driving significant operational transformation and superior user experiences across our global client base.

Key Responsibilities :

- Architect and oversee the end-to-end development of autonomous AI agents capable of complex reasoning and multi-modal task execution to automate high-value business workflows.

- Lead the integration of advanced LLM frameworks and orchestration layers to ensure agents maintain context, accuracy, and alignment with enterprise security standards.

- Establish robust MLOps and evaluation pipelines using tools like MLflow and LangSmith to monitor agent performance, drift, and reliability in production environments.

- Mentor cross-functional engineering teams on best practices for prompt engineering, fine-tuning, and the implementation of neural network architectures to foster a culture of technical excellence.

- Partner with stakeholders to identify high-impact use cases for Generative AI, ensuring that technical roadmaps directly contribute to measurable business outcomes and competitive differentiation.

Required Skillset :

- Demonstrated expertise in designing and scaling Agentic AI and Gen AI solutions, with a deep understanding of the underlying mechanics of LLMs and their application in real-world scenarios.

- Proven ability to architect complex systems using Natural Language Processing and neural networks, ensuring seamless interaction between AI agents and existing enterprise software stacks.

- Strong proficiency in operationalizing AI models through tools such as MLflow and LangSmith, with a focus on observability, version control, and continuous improvement.

- Exceptional communication skills, with the ability to articulate complex technical strategies to non-technical stakeholders and influence decision-making at the leadership level.

- A collaborative mindset that thrives in a hybrid work environment, capable of leading distributed teams across Hyderabad, Bangalore, or Chennai with agility and precision.

- A solid academic foundation in Computer Science, Artificial Intelligence, or a related quantitative field, complemented by 8 to 13 years of progressive experience in the AI/ML domain.