Senior Forward Deployed Engineer, Sr FDE (L5) - Databricks

EducationPals; India; Remote; INR 4,000,000 - 6,000,000; Full time

Job summary

EducationPals in India is seeking a Senior Forward Deployed Engineer to work with customers, architect solutions, and productionize data and AI workloads on the Databricks platform.

You will own the architecture, lead design decisions, and deliver end-to-end systems spanning data engineering, AI, and application development. This remote role emphasizes collaboration across teams.

Qualifications

• Experience building data & AI solutions for enterprise customers.
• Strong cloud engineering and data pipeline skills.
• Experience with production-grade AI systems is a plus.

Responsibilities

• Build and productionize data and AI solutions on the Databricks platform for customers.
• Own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development.
• Work cross-functionally to ensure scalable, reliable solutions.
• Design retrieval-augmented generation interfaces for agents and ensure safe external access.
• Instrument observability, debugging, and failure recovery in production.

Skills

AI fundamentals

Python

MLOps

Cloud

Tools

Databricks

Job description

OverviewCultureBenefitsDiversityEngineeringResearchStudents & new grads Back to search results Senior Forward Deployed Engineer, Sr FDE (L5) Remote - India As a Senior Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally

Relevance is based on skills and concepts, not a guarantee that you qualify.

Covered skills: AI fundamentals Python MLOps Cloud

Skills to close: None listed

Build the skills for this job

Coming-soon courses matched to this posting: outline, waitlist, and skill path.

Understand the core components that distinguish agentic systems from single-response LLM applications.

2. Tool Integration and API Design

Build structured interfaces that allow agents to interact safely with external systems and services.

3. Retrieval-Augmented Generation for Agents

Ground agent actions in trusted knowledge using vector search and context retrieval patterns.

4. Permissions, Governance, and Human Oversight

Implement controls that prevent agents from taking unauthorized or high-risk actions without approval.

5. Observability and Debugging Agent Workflows

Instrument agent systems to understand behavior, diagnose failures, and improve reliability over time.

6. Failure Recovery and Reliability Patterns

Design agents that handle errors gracefully and recover from unexpected conditions in production.

7. Testing and Evaluating Agent Systems

Establish test suites and evaluation frameworks to validate agent behavior before and after deployment.

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