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SeniorOfficeIndia Remote

Technical Specialist

D
DevRev
Уровень
Senior
Формат
Office
О роли

Описание вакансии

About the company

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.

Responsibilities
  • Lead technical discovery: map customer workflows, systems of record, and failure modes; identify where agentic automation creates measurable economic impact (cost per case, resolution time, deflection).
  • Build and deliver PoCs and proofs of value on live customer data and systems — not canned environments.
  • Translate business problems into agent architectures: orchestration design, state management, tool/skill decomposition, guardrails, and escalation paths.
  • Shape SOWs, solution designs, and delivery plans with defensible technical scope and effort estimates.
  • Implement production agents on the DevRev platform: agent instructions, deterministic workflows, skills, and integrations with enterprise systems (CRM, ERP, payments, core operational APIs).
  • Own reliability: design evaluation harnesses, debug agent failures (hallucination, state drift, loops, guardrail leakage), and iterate to production-grade adoption.
  • Drive integration work hands-on — REST APIs, webhooks, auth flows, data mapping — in collaboration with Product and Engineering.
  • Instrument and report outcomes: adoption, containment, accuracy, and cost metrics that stand up in a QBR.
  • Convert engagement learnings into reusable assets: reference architectures, playbooks, sandbox environments, and internal tooling.
  • Enable partner engineers and integrators to deliver independently; run workshops and bootcamps.
  • Feed structured field signal to Product: what breaks, what's missing, what competitors are doing.
Requirements
  • 8–10 years in customer-facing technical roles (forward-deployed / field engineering, solution delivery, technical specialist roles) in B2B SaaS or enterprise software.
  • Hands-on experience building LLM-based systems in production: agent orchestration, prompt and context engineering, RAG, tool/function calling, and evaluation. You have shipped something real, with users, and can walk us through its failure modes.
  • Strong engineering fundamentals: proficient in Python or JavaScript/TypeScript; fluent with REST APIs, webhooks, and integration patterns; comfortable with SQL and working directly in customer data.
  • Strong discovery and solutioning craft: stakeholder workshops, PoCs, and technical scoping with clear effort estimates.
  • Executive-grade communication: you can whiteboard an architecture for engineers and frame ROI for a CXO in the same meeting.
  • Operates well in ambiguity: unstructured environments, contested stakeholder maps, shifting scope. Bias to ownership.

Strong plus:

  • Experience with deterministic workflow / state-machine design for AI agents, and with making non-deterministic systems reliable enough for regulated or high-volume operations.
  • Production experience in complex enterprise domains: airlines, BFSI, telecom, manufacturing, or similar multi-system environments.
  • Familiarity with CRM/CX platforms (Salesforce, Zendesk, ServiceNow), cloud platforms (AWS/Azure/GCP), and modern DevOps tooling.
  • Exposure to AI-assisted development workflows (Cursor, Copilot, Claude Code).
Conditions
  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • This is a customer-embedded role: you will be based on-site at client locations, working face-to-face with customer teams as the default mode of operation — not remote-first with occasional visits. Expect sustained, full-time presence at the customer's offices for the duration of each engagement.
Стек и навыки

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