Forward Deployed Engineer- Gen AI

What Youll Do

• Customer-facing: 30% working directly with customers.
• Coding & Integration: 70-80% hands-on technical implementation
• Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers existing tech stacks and workflows.
• Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
• Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
• Own Data Insights: Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
• Prototype & Iterate: Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
  
  

What You Bring

• Experience: 3+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus.
• Background: Bachelors or Masters degree in Computer Science, Engineering, or a related technical field.
• Coding Skills: Strong proficiency in TypeScript/JavaScript, Python, data structures and algorithms. (Nice to have: Go)
• Applied AI Knowledge: Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
• Integration Expertise: Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
• Cloud & Deployment: Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
• Data Transformation: Skilled in data mapping, schema alignment, and working with heterogeneous systems. Understanding of data modeling and graph data structures.
  
  

Technical Skills

API integrations (calling & building): REST API design, building, and consumption, Webhooks - building and handling, Microservices architecture, Event-driven architecture, GraphQL

Languages: TypeScript / Python, JavaScript / Node.js, SQL

Databases: PostgreSQL, Redis (caching, queuing), MongoDB, Vector databases

AI and LLM: LangChain, RAG pipelines, Embeddings and vector search, Prompt engineering, LLM API usage (OpenAI, Anthropic), MCP Servers

Testing and Observability: Unit testing (JUnit, pytest, Mockito), API testing (Postman), Monitoring tools - Grafana, Prometheus, Coralogix

Building customer workflows and automations

Cloud & DevOps: AWS basics - S3, Lambda, ECS, CloudWatch, Docker, Kubernetes, Git / version control.

Customer-Facing Experience

Has built customer flows or integrations

Improvement work tied to customer outcomes

Direct customer interaction in past roles

Understanding the Customers Problem

Integration Work (Imp - connect two systems, work with 3rd party APIs, built/configured webhooks)

Handling Real Customer Issues (post-deployment)

Communication with Non-Technical Stakeholders & POC / Prototype Delivery.

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