Note: The job is a remote job and is open to candidates in USA. Tango Analytics is focused on leveraging technology and data to enhance business decision-making. They are seeking an AI Workflow Engineer to build and implement AI tools across various internal functions, ensuring these tools are integrated into real workflows to drive business impact.
Responsibilities
- Ship AI tools that move function KPIs
- Build and ship internal AI tools and automations across function clusters (Finance/RevOps and Go-To-Market first) sequenced to where the business impact is highest
- For each shipped tool, define a named owner function, a measured baseline, and a per-tool annualized value target
- Before building, challenge whether buying is the better path. Bring a clear build-versus-buy recommendation for every tool, and only build when the case for build is stronger than the case for buy
- Establish eval harnesses, monitoring, and guardrails for each shipped tool, covering accuracy, safety, cost, and latency
- Operate as a force multiplier through AI agents and platforms
- Direct an autonomous coding agent (Devin or equivalent) as a backlog-driven contributor; orchestrate the agent’s work alongside your own coding rather than treating it as a coding-assistant only
- Maintain and continuously upgrade a personal AI-engineering setup (e.g. Claude Code, MCP servers, custom skills, worktrees, multi-agent workflows) and share patterns that raise the productivity of other Tango engineers
- Architect the AI platform layer for Tango, in partnership with the rest of Engineering
- Partner with Tango’s broader Engineering organization (Product Engineering, Platform, Data) to design and build the reusable AI platform layer: eval frameworks, retrieval stacks, model gateways, guardrails, and AI FinOps (model spend, usage attribution, cost and latency budgeting) that any team at Tango can pick up
- Drive shared AI architecture decisions across teams; reconcile build-versus-buy choices on model providers, hosting options, and vector infrastructure with the rest of Engineering rather than in isolation
- Track frontier-model capability and select what is actually useful for Tango; partner with Security, Legal, and Compliance on AI governance patterns including data handling, prompt-injection defense, and PII safety
- Embed across function clusters to land AI in real workflows
- Embed with Finance/RevOps and Go-To-Market tiger teams in sequence; AI work has to land inside each function’s workflow, not as an isolated central-team output
- Pair with function leaders to identify the highest-leverage AI use cases, then ship them; raise the AI literacy of each function through brown bags, working sessions, and review feedback
Skills
- 8+ years of professional software-engineering experience, including 4+ years shipping AI-powered features or AI-native tools to production
- Experience building internal AI tools across various business departments
- AI-first, Claude-Code-first workflow. Your primary day-to-day workflow is built around Claude Code or an equivalent agentic coding tool — it is your default starting point for every task, not a tab-autocomplete add-on
- Literate in agentic-tooling beyond coding agents. Hands-on experience with at least one autonomous coding-agent or AI-engineer platform such as Devin, Manus, Aider, or equivalent, and the ability to articulate where these platforms help and where a human engineer is still required
- Multi-agent workflow habits. Comfortable running multiple AI sessions in parallel, maintaining personal skills and MCP servers, and orchestrating an agent backlog rather than coding linearly
- Production experience with LLM APIs (Anthropic, OpenAI), including prompt design, RAG, function calling / tool use, evals, prompt caching, and reasoning about cost / latency / safety trade-offs
- Strong general software-engineering fundamentals. You can write code without AI when needed, debug production failures, and reason about correctness, concurrency, and data flow at the level expected of a Staff engineer
- Demonstrated ability to embed with non-engineering teams (Finance, GTM, Operations, HR, Legal) and translate business problems into AI-assisted workflows
- Pace of adoption and a learn-out-loud disposition. AI tooling moves weekly; you keep up and share what you learn with the broader Engineering organization
- Bachelor's Degree in Computer Science, or a related field
- SaaS start-up experience is highly desired (building the Labs function from scratch)
- Prior experience standing up an internal AI platform, AI lab, or 'AI for internal employees' function at a previous company
Benefits
- Health, dental, and vision insurance
- A 401(k) plan with company match
- Generous paid time off to support your well-being
- Flexible Work Environment Whether remote, hybrid, or in-office, we support work arrangements that promote productivity and balance
- Inclusive & Collaborative Culture We foster a workplace where diverse perspectives are valued, teamwork is encouraged, and everyone has a voice
Company Overview