Forward Deployed Engineer - Applied AI

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Навык востребован (python). Но вилки нет, про деньги придётся договариваться с нуля.

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Наша компания

At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. Forward Deployed Engineer As a Forward Deployed Engineer at DevRev, you will work closely with our pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc. One of the key functions of this role is, building the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/ or real-time communication architectures. You will be expected to employ your creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes.

Чем предстоит заниматься

Customer-facing: 30% working directly with customers

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

Lead Cross-functional Collaboration: Maintain constant communication loops with customers, engineering, product, customer success, support, and revenue teams to ensure alignment

Guide Technical Adoption: Learn and master new tools, then guide customers through critical workflows like code repository integrations and advanced configurations

Travel Ready: Willingness to travel up to 30% for on-site implementations, technical workshops, and customer engagements

Наши требования

Experience: 5+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus

Coding Skills: Strong proficiency in TypeScript, JavaScript, Python, data structures and algorithms. (Nice to have: Go)

Design & Deploy AI Agents: Build and configure intelligent solutions leveraging snap-ins, connectors (AirSync), workflows, and AI agents on the DevRev platform to solve real customer problems

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: 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

Observability: Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution

Context-Aware Systems: Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations

Strong written and verbal skills

Background: Bachelor's or Master’s degree in Computer Science, Engineering, or related discipline. Advanced degrees or certifications in AI/architecture frameworks (e.g., TOGAF, SAFe) are a plus