Sr. Agentic AI Engineer

Please note :

This is an on site position in Kharadi, Pune.

Timings : 6 PM - 3 AM

Remote / Hybrid options are not available

Notice Period - Immediate joiners or those with a maximum notice period of 30 days are preferred.

We’re a fast-growing AI startup with a fast-paced, ambitious culture. Our team often works long hours (at times 12 hours a day, 6 days a week), similar to other high-growth tech companies. If you thrive in this kind of environment, we’d love to hear from you!

About Jeeva.AI

Jeeva AI is a superhuman Agentic AI that takes the grunt work out of sales, autonomously discovering and enriching high intent leads, crafting hyper personalized outreach, managing smart follow-ups, and handling objections so your reps focus on what they do best : closing deals.

Trusted by 500+ B2B companies to generate over $50 M in pipeline, Jeeva delivers a consistent 24 / 7 revenue engine and gives you 50 qualified prospects free during your demo.

As a dynamic startup we are backed by Alt Capital (founded by Jack Altman & Sam Altman), Marc Benioff (CEO Salesforce), Gokul (Board Coinbase), Bonfire (investors in ChowNow), Techstars (investors in Uber), Sapphire (investors in LinkedIn), Microsoft with $4.5M ARR in just 9 months after launch, we’re not just growing - we’re thriving and making a significant impact in the world of artificial intelligence.

Responsibilities & Expectations :

Proven experience in developing AI agents, generative AI applications, or multi-agent systems.

Expertise in Large Language Models (LLMs) such as GPT, T5, BERT, etc., and experience with transformer architectures.

Hands-on experience with Retrieval-Augmented Generation (RAG) and Agentic RAG frameworks.

Familiarity with agent-based frameworks (e.g., OpenAI Gym, LangChain, Rasa, Ray RLLib, etc.).

Experience in reinforcement learning, supervised learning, and unsupervised learning to enhance agent capabilities.

Proficiency in NLP techniques and frameworks (e.g., spaCy, Hugging Face Transformers).

Strong coding skills in Python, with experience using libraries such as TensorFlow, PyTorch, and Hugging Face for AI model development.

Experience with cloud platforms (AWS, GCP, Azure) for scalable deployment and containerization (e.g., Docker, Kubernetes).

Ability to innovate and solve complex problems in real-world settings using generative models and intelligent agents.

Strong communication skills and the ability to work in cross-functional teams, collaborating with data scientists, product managers, and other stakeholders.

Ability to integrate external data sources, APIs, or databases into AI agent workflows for dynamic decision-making and knowledge retrieval.