Forward Deployed Engineer
Hands-on with LLMs, prompt engineering, RAG and building AI agents/integrations—directly applies AI tooling for fast prototyping and customer demos.
About the Role
Forward Deployed Engineer responsible for building integrations, AI agents, and a Knowledge Graph connecting DevRev with customers' SaaS and non‑SaaS systems. The role combines ~70–80% hands‑on development (TypeScript, JavaScript, Python), data analysis, and ~30% customer‑facing work with up to 80% travel for on‑site implementations.
Job Description
Role
Forward Deployed Engineer working with pre- and post-sales Customer Experience to design, develop, and deploy solutions on top of the core platform (DevRev). The role focuses on building a Knowledge Graph and integrations that connect customers’ tech stacks via APIs, webhooks, and real-time architectures, and on applying AI and analytics to customer workflows.
Key Responsibilities
- Customer-facing engagement (~30%) including live technical demos, workshops, and requirements gathering.
- Hands-on coding and integration (~70–80%): design, develop, and launch AI agents, integrations, and automations.
- Build and maintain integrations between DevRev and SaaS/non‑SaaS systems using APIs, webhooks, and event-driven architectures.
- Optimize AI performance through prompt engineering, semantic search tuning, RAG and function-calling approaches, and building evals to validate agents.
- Write SQL queries, perform data analysis, and build dashboards to surface actionable insights.
- Rapid prototyping and iteration: create proofs-of-concept and refine solutions based on customer feedback.
- Lead cross-functional collaboration with engineering, product, customer success, support, and revenue teams.
- Guide customers through technical adoption including repository integrations and advanced configurations.
- Travel up to 80% for on-site implementations, technical workshops, and customer engagements.
Requirements
- 5+ years of experience in software development, systems integration, or platform engineering.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- Strong proficiency in TypeScript/JavaScript and Python; Go is a plus.
- Applied AI knowledge: familiarity with large language models (LLMs), prompt engineering, RAG, function calling, and building evals for agent validation.
- Integration expertise with large-scale data synchronization, API integration patterns (REST, GraphQL, webhooks), and event-driven/pub-sub architectures.
- Cloud and deployment experience with serverless and edge platforms (e.g., AWS Lambda, Google Cloud Functions), containers, CI/CD, and observability practices.
- Data skills: SQL, data mapping, schema alignment, data modeling, and experience with graph data structures.
- Experience implementing logging, error surfacing, and telemetry for observability and debugging.
- Familiarity with Model Context Programming (MCP) or context-aware system design is a plus.
- Strong documentation, written and verbal communication skills, and ability to triage and unblock technical and non-technical issues.
Other Notes
- Shortlisted candidates will undergo Background Verification (BGV).
- Role requires significant travel readiness (up to 80%).