Senior Forward Deployed Engineer
Posted 2 days ago
The role in short
Architect, build, and deploy production-grade AI integrations and solutions for enterprise customers, acting as the technical lead for discovery, implementation, and ongoing reliability.
About the Role
As a Senior Forward Deployed Engineer at Blue Machines, you’ll own the full lifecycle of integrations between our AI platform and enterprise customer systems, from solution design through production rollout and ongoing reliability. You’ll be the technical lead on customer deployments, working across APIs, cloud infrastructure, and AI frameworks (like LangChain and LLM APIs) to ship intelligent, scalable, production-grade solutions. You’ll also help shape our integration playbook and mentor other engineers.
What You’ll Do
- Architect, build, and own complex integrations using REST APIs, WebSockets, and webhooks, with a focus on scalability, low latency, and fault tolerance
- Design and deploy production solutions on cloud platforms (GCP / AWS / Azure), including networking, security, and cost decisions
- Lead integration of AI/LLM capabilities (LangChain, OpenAI, Anthropic, or similar SDKs) into customer workflows, including prompt design, orchestration, and evaluation
- Act as the main technical contact for enterprise customers: run discovery, translate business requirements into technical solutions, and drive deployments to go-live
- Debug and resolve critical production issues across distributed systems, and lead root-cause analysis
- Set up observability, monitoring, and alerting for integration workflows, and drive automation and documentation standards
- Build reusable connectors, frameworks, and best practices that speed up future deployments
- Mentor engineers and work with Product and Engineering to feed customer insights into the platform roadmap
- Travel to customer sites as needed (roughly 10–20%)
What You’ll Bring
- 5–8 years of software engineering experience, including at least 2–3 years in customer-facing, solutions, or integration engineering roles
- Strong expertise in Python or Java for backend services and integrations
- Required: deep hands-on experience deploying and operating production workloads on a major cloud platform (GCP preferred)
- A proven track record of designing and shipping large-scale integrations with enterprise systems (CRMs, contact center platforms, ERPs, internal APIs)
- Strong command of API design and authentication/authorization protocols (OAuth2, JWT, SAML/SSO, mTLS)
- Practical experience building with AI/LLM ecosystems (prompt engineering, RAG, LangChain-style orchestration, or agent frameworks)
- Strong system design skills, with experience making trade-offs around performance, reliability, and security
- Excellent problem-solving and communication skills, including comfort working directly with senior customer stakeholders
Bonus Points: Healthcare Experience
- Experience building or deploying software in healthcare, health tech, or digital health
- Familiarity with healthcare interoperability standards (HL7 v2, FHIR) and EHR integrations (Epic, Oracle Health/Cerner, athenahealth)
- Working knowledge of HIPAA, handling of PHI, and compliance frameworks such as SOC 2 or HITRUST
- Exposure to provider, payer, or patient-engagement workflows (scheduling, prior authorization, care coordination, patient outreach)
Also Nice to Have
- Experience with telephony and real-time communication (SIP, WebRTC, Twilio, Genesys, Five9, Amazon Connect, Avaya) and voice AI pipelines (ASR/TTS)
- Hands-on experience with Postman, Wireshark, and observability stacks (Datadog, Grafana, Prometheus, OpenTelemetry)
- Strong grasp of CI/CD, containerization (Docker), and orchestration (Kubernetes)
- Prior experience as a Forward Deployed Engineer, Solutions Architect, or Technical Consultant at a high-growth startup
Equal Opportunity
Blue Machines is an equal opportunity employer. We welcome applicants of every race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. Qualified applicants with arrest and conviction records will be considered in line with the San Francisco Fair Chance Ordinance.
Prep for this interview
5 questions likely to come up at Blue Machines AI, each matched to a line in this posting.
- 1Cloud, deployment and security
They wrote: “Design and deploy production solutions on cloud platforms (GCP / AWS / Azure), including networking, security, and cost decisions”
The customer's security team sends a 200-question review. How do you handle it?
How to answer
Why they ask: Security reviews often block deals. FDEs help get through them.
- Start from your company's standard answers (SOC 2 report, past reviews)
- Answer clearly; don't oversell
- Bring in your security team for anything you're unsure of
- Keep the new answers for the next customer
Tip: Reuse past answers, flag honest gaps, and offer a call for the hard questions.
- 2Integrations and APIs
They wrote: “Architect, build, and own complex integrations using REST APIs, WebSockets, and webhooks, with a focus on scalability, low latency, and fault tolerance”
Walk me through connecting our product to a customer's internal system that has no documentation.
How to answer
Why they ask: This happens weekly in the job. They want a calm, step-by-step method.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- Agree on how failures get reported, and who fixes what
Tip: Talk about finding the owner of the system first. The code is the easy part.
- 3LLMs, RAG and agents
They wrote: “Practical experience building with AI/LLM ecosystems (prompt engineering, RAG, LangChain-style orchestration, or agent frameworks)”
A customer wants a chatbot over their internal documents. How do you build it?
How to answer
Why they ask: RAG is the most common first project. They want the whole path, from messy files to answers people trust.
- Collect and clean the documents; handle permissions per user
- Split them into chunks, embed, and store with source links
- Retrieve, then answer with citations; say “I don't know” when retrieval is weak
- Build a test set of real questions with expected answers before launch
Tip: Spend more time on the data and on testing than on the model.
- 4Discovery and scoping
They wrote: “Act as the main technical contact for enterprise customers: run discovery, translate business requirements into technical solutions, and drive deployments to go-live”
A customer says “we want AI in our claims process.” What do you ask in the first meeting?
How to answer
Why they ask: Most FDE work starts this vague. They want to hear you find the real problem before you pick a tool.
- Map the current process: who touches a claim, in what order, with which systems
- Find the slowest or most error-prone step and ask what it costs them
- Agree on one measurable goal (for example time per claim, or error rate)
- Ask what data you can access, and who signs off on security
Tip: Ask about the work, not the technology. Who does it today, how long it takes, what a mistake costs, and how they'd know it got better.
- 5Coding
They wrote: “Strong expertise in Python or Java for backend services and integrations”
Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.
How to answer
Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.
- Read with a proper CSV parser; check the header first
- Validate each row and collect errors, not crash on the first one
- Send in batches with retries and a clear report at the end
- Write one or two quick tests for the parsing
Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.
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