Forward Deployed Engineer

Blue Orange Digital•Miami, FL

22d•$150,000 - $185,000•Remote

About The Position

Blue Orange Digital is seeking a Forward Deployed Engineer to embed directly into client organizations. This role involves understanding messy real-world processes, translating them into agentic AI workflows, and building production-grade solutions. You will act as a bridge between business stakeholders and technical teams, mapping processes in the morning and wiring them into agents in the afternoon. The role requires a balance of discovery, facilitation, trust-building, and hands-on engineering, with a focus on shipping functional workflows, not just prototypes. You will be responsible for building agent logic, integrations, and evaluation systems, ensuring the client can run and extend the delivered solutions.

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

Nice To Haves

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)

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

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