Forward Deployed Engineer

Blue Orange Digital · New York, NY · 2 wk ago

On-siteEngineering$150k–$185k/yrFull-time

Position Overview

This is the person we send into a client when the problem is not yet a spec. You sit with their operators, finance leads, and analysts, watch how work actually gets done, and turn messy real-world processes into agentic AI workflows that hold up in production.

You are dual-fluent by design. In the morning you map a claims-handling or order-to-cash process with a business owner who has never written a line of code. In the afternoon you wire that process into an agent that calls their CRM, queries their warehouse, and routes exceptions to the right human. You translate in both directions, turning vague business pain into concrete technical scope, and turning technical constraints into options a non-technical stakeholder can decide on.

Responsibilities

Embed with client teams to understand how work actually happens, shadowing operators and mapping processes that live in people's heads, spreadsheets, and a dozen disconnected tools
Break down complex business processes into agentic workflows: decompose a goal into steps, decide what an agent automates versus where a human stays in the loop, and design the tool-use and decision logic to match
Build production-grade agentic workflows using frameworks like LangGraph and LangChain, including tool calling, memory, routing, retries, and clean failure recovery
Build integrations to the data and operational systems that workflows depend on: CRMs, ERPs, ticketing systems, data warehouses, internal APIs, and document stores, handling auth, rate limits, and reliability
Enable core platform capabilities that the whole engagement reuses: retrieval over client documents, structured output and function calling, prompt versioning, logging, and observability
Design evaluation and guardrails that make a workflow trustworthy in an enterprise setting: task-specific evals, regression checks, PII handling, and human review steps where the stakes demand them
Run working sessions and demos that keep business stakeholders bought in, translating technical tradeoffs into clear decisions about cost, risk, and timeline
Document what you build and hand it over cleanly, so client teams can operate and extend the workflows after the engagement
Bring patterns back to BOD, turning what worked on one engagement into reusable building blocks for the next

Requirements

3 or more years of software engineering experience building systems that run in production, plus the judgment to know what production-ready means
Hands-on experience building with LLMs: prompting, function calling, structured output, retrieval, and at least one agent or multi-step workflow you took past the prototype stage
Strong integration skills, you have connected real systems through REST APIs, webhooks, SDKs, and databases, and dealt with auth, pagination, rate limits, and flaky upstreams
Proficiency in Python, comfort with async patterns, API design, and the data-pipeline reliability that agentic workflows live or die on
Working knowledge of SQL and data systems, enough to pull what a workflow needs from a client's warehouse or operational database
Real client-facing or cross-functional skill: you can sit with a non-technical stakeholder, draw out how their process works, and earn their trust without talking down to them
Strong written and verbal communication, you can explain why an agent took a wrong turn, or why a manual step should stay manual, to a business owner without losing them
A bias toward shipping, you would rather get a working workflow in front of users this week than perfect an architecture diagram
Production experience with agent frameworks (LangGraph, AutoGen, CrewAI) or building custom orchestration
Experience with RAG systems: chunking, embeddings, vector stores (Pinecone, Weaviate, Qdrant, pgvector), and re-ranking

Preferred Qualifications

Familiarity with LLM evaluation: task-specific metrics, LLM-as-judge, and regression test suites
Background in process mapping, solutions engineering, forward-deployed work, or technical consulting across concurrent engagements
Experience with workflow and integration platforms (Temporal, Airflow, Zapier, n8n) or iPaaS tooling
Exposure to a major cloud and its AI services (AWS Bedrock or SageMaker, GCP Vertex AI, Azure ML)

Benefits

Competitive compensation with performance bonuses
Problems that matter, real client processes with real constraints, not greenfield sandboxes
A front-row seat to how a dozen industries actually run, and the chance to automate the parts that slow them down
Direct access to modern AI infrastructure: AWS, GCP, Azure, Databricks, Snowflake, and the open-source ecosystem
Builder culture where engineers lead and ship, with no bureaucracy between you and the work
Professional development budget and certification support
Flexible remote work environment
A team that will push back on your design decisions and make them better
Unlimited Paid Time Off (PTO)
Paid parental/bereavement leave

About Blue Orange Digital

Blue Orange Digital is a data and AI consulting firm that helps companies turn complex data into real business outcomes. We partner with organizations across industries to design and deploy scalable data infrastructure, advanced analytics, and AI-powered solutions. Our team is fully remote, globally distributed, and driven by curiosity, impact, and innovation.