C
Forward Deployed Engineer- Gen AI
Cloudesign
Bengaluru · On-site Full-time Mid Level 4d ago
About the role
What You'll 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: Bachelor's or Master's 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 Customer's 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.
Requirements
- Strong proficiency in TypeScript/JavaScript, Python, data structures and algorithms.
- Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
- Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
- Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
- Skilled in data mapping, schema alignment, and working with heterogeneous systems.
- Understanding of data modeling and graph data structures.
Responsibilities
- Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows.
- Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
- Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
- Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
- Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
Skills
AWS LambdaAWS S3CloudWatchContainersDockerEmbeddings and vector searchEvent-driven architectureFunction callingGenerative AIGitGoGoogle Cloud FunctionsGrafanaGraphQLJUnitKubernetesLangChainLLM API usageMicroservices architectureMonitoring toolsNode.jsObservabilityOpenAIPostmanPostgreSQLPrompt engineeringPrometheusPythonRAG pipelinesREST API designRedisServerless platformsSQLTypeScriptUnit testingVector databasesWebhooks
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