We are seeking an experienced and technically proficient AI and Databricks Engineer with 4+ years of specialized experience to drive the development and deployment of industrial-grade Large Language Model (LLM) and Generative AI applications. This role requires mandatory, hands-on expertise in the entire Databricks ecosystem combined with deep skills in Python and modern AI frameworks. The successful candidate will be critical in architecting, securing, and scaling our Gen-AI solutions from our Pune or Nagpur office.

Role Requirements & Logistics

Experience Required : 4+ years of professional experience.

Location : Nagpur or Pune, Maharashtra (Work from Office).

Job Type : Full-time.

Education : Degree in Computer Science or a similar major is required.

Key Responsibilities & Technical Deliverables :

LLM Systems & Advanced AI Development :

- Application Development : Design, develop, and deploy industry-grade LLM and Gen-AI applications using major providers such as OpenAI, Anthropic (Claude), or other foundational models.

- Agentic Architectures : Utilize Python expertise and frameworks like LangChain and LlamaIndex to build sophisticated autonomous Gen-AI solutions and agentic architectures.

- Advanced Techniques : Implement and optimize complex retrieval strategies including RAG (Retrieval-Augmented Generation), ARAG, and CAG. Apply techniques like A/B testing and reinforcement learning for continuous model improvement.

- Integration : Architect and execute robust processes for integrating LLM systems with enterprise APIs and diverse data sources.

Databricks Platform & MLOps :

- Databricks Mastery (Mandatory) : Demonstrate mandatory, hands-on experience across the entire Databricks platform, including Spark, Delta Lake, MLflow, Databricks Notebooks, and Unity Catalog.

- Vector Database Integration : Implement and manage integrations with various vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS) to power efficient and scalable RAG pipelines.

- Governance & Scalability : Maintain a solid understanding of data governance, security, and scalability within the Databricks environment.

Cloud Environments & Engineering Standards :

- Cloud Proficiency : Possess rich experience working within major cloud environments (Azure, AWS, or GCP) and integrating with their native AI/ML services.

- Mentorship : Provide technical guidance and mentorship, particularly to junior team members (including the 1-2 resources with 1 year experience who will be trained on the project).