Senior/Staff Forward Deployed Engineer

💻 Remote | LatAm - WE ARE EXCLUSIVELY CONSIDERING APPLICATIONS FROM INDIVIDUALS CURRENTLY RESIDING IN LATAM.

❗️ONLY ENGLISH RESUMES WILL BE CONSIDERED

🗣️ PLEASE NOTE THAT THIS ROLE REQUIRES ENGLISH PROFICIENCY (C1-C2 LEVEL)

About Motum

Motum connects experienced developers, engineers, and technical professionals with US companies building committed, long-term tech teams. Our roles are fully remote and full-time, designed for people who want real ownership, meaningful work, and the opportunity to grow inside US-based dynamic teams.

When you join Motum, you work full-time with one company, integrate directly into their team, and build a career with long-term impact. Ready to join us?

About the Client

Our client is a fast-growing US HealthTech AI company building intelligent software that helps healthcare organizations automate complex workflows and make better use of clinical and operational data.

Its AI platform works across healthcare data, documents, internal systems, and workflows to help providers and healthcare organizations reduce manual work, surface critical information faster, and improve operational efficiency.

The company is expanding how it uses generative AI across areas such as clinical documentation, healthcare operations, data retrieval, workflow automation, and decision-support tools.

You will join a highly technical, product-driven team where AI is already part of the core product. Because the platform operates in a healthcare environment, reliability, data privacy, security, and accuracy are essential.

About the Role

We are looking for a Senior / Staff Forward Deployed Engineer who can combine strong software engineering skills with exceptional customer-facing ability.

You will work directly with healthcare customers to understand complex technical and operational problems, rapidly prototype AI-powered solutions, and then turn those prototypes into reliable production systems.

This is not a traditional implementation or solutions engineering role.

You will write production code, design technical architectures, integrate complex customer systems, troubleshoot real-world environments, and own solutions from initial discovery through deployment.

You will also serve as a technical bridge between customers and the client's Product and Engineering teams, helping translate real customer problems into scalable product capabilities.

This role is ideal for an engineer who enjoys being close to both the technology and the customer and who can move comfortably between a customer conversation, architecture discussion, prototype, and production deployment.

Responsibilities

• Work directly with healthcare customers to understand their technical environments, workflows, data, and business problems
• Lead technical discovery sessions with engineering, product, operations, and customer stakeholders
• Build AI-powered prototypes and proof-of-concepts that demonstrate how the platform can solve real customer problems
• Turn successful prototypes into reliable, production-ready applications and integrations
• Design and build backend services using Python, APIs, databases, and modern cloud infrastructure
• Build applications using LLMs, RAG, agents, tool calling, structured outputs, and external data sources
• Integrate customer APIs, EHR-related systems, databases, data warehouses, internal services, and third-party platforms
• Design retrieval pipelines involving document ingestion, embeddings, vector databases, metadata filtering, and reranking
• Develop AI agents capable of interacting with APIs, databases, internal tools, and external systems
• Troubleshoot complex customer environments, integration issues, model behavior, data quality problems, and production failures
• Design safeguards and validation mechanisms for AI systems operating with sensitive healthcare information
• Own solutions from technical discovery and architecture through implementation, testing, deployment, and iteration
• Communicate technical tradeoffs clearly to both technical and non-technical customer stakeholders
• Partner closely with Product and Engineering to identify recurring customer needs and influence the product roadmap
• Help establish best practices for deploying, monitoring, evaluating, and improving customer-facing AI systems
• Mentor engineers and contribute to architecture decisions at the Senior or Staff level

Qualifications

• 6+ years of professional software engineering, backend engineering, machine learning engineering, or applied AI experience
• Candidates being considered at the Staff level should typically have 8+ years of professional engineering experience with significant technical ownership
• 2+ years of hands-on experience building applications with large language models or generative AI
• 2+ years working in a customer-facing engineering, solutions engineering, forward deployed engineering, consulting, implementation engineering, or similar technical role
• Proven experience shipping software products, platforms, or major technical features into production
• Advanced proficiency with Python
• Strong experience with TypeScript and/or JavaScript
• Hands-on experience building production applications using OpenAI, Anthropic, or comparable LLM APIs
• Strong understanding of RAG architecture, embeddings, vector search, document processing, retrieval, and reranking
• Experience building AI agents, tool-calling workflows, or multi-step AI systems
• Strong experience designing and consuming REST APIs
• Experience building backend services with frameworks such as FastAPI
• Strong working knowledge of SQL and PostgreSQL
• Experience integrating external APIs, databases, SaaS platforms, and customer systems
• Experience with at least one vector database or vector search technology such as pgvector, Pinecone, Weaviate, or OpenSearch
• Experience deploying production applications on AWS, GCP, or Azure
• Proficiency with Git and Docker
• Strong debugging and troubleshooting skills across distributed systems and customer environments
• Proven ability to independently take a technical problem from ambiguity through architecture, implementation, and deployment
• Excellent written and verbal communication skills
• Ability to explain technical concepts, architecture decisions, and tradeoffs clearly to customers

Nice To Have

• Experience working in HealthTech, healthcare SaaS, digital health, clinical software, healthcare operations, or medical technology
• Experience integrating with EHR/EMR platforms, healthcare APIs, FHIR, HL7, or clinical data systems
• Familiarity with HIPAA, healthcare data privacy, PHI, security controls, or regulated software environments
• Experience with AI agents, LangGraph, MCP, LangChain, or LlamaIndex
• Experience with Pinecone, Weaviate, pgvector, or OpenSearch
• Experience designing agent orchestration, tool-use, memory, and state management systems
• Experience building automated LLM evaluation frameworks and regression testing
• Experience evaluating retrieval quality, hallucination rates, task completion, latency, and model cost
• Experience with multimodal AI, OCR, document intelligence, or medical document processing
• Experience with hybrid search, knowledge graphs, or advanced retrieval architectures
• Familiarity with observability tools and production AI monitoring
• Experience with Kubernetes, Terraform, CI/CD, or infrastructure-as-code
• Previous experience working directly with US enterprise customers
• Startup experience in a highly autonomous engineering environment

Tech Stack

Python | TypeScript | JavaScript | LLMs | RAG | OpenAI | Anthropic | LangGraph | LangChain | LlamaIndex | MCP | Vector Databases | pgvector | Pinecone | Weaviate | APIs | FastAPI | PostgreSQL | Docker | AWS | Azure | GCP

We Offer

• 🏡 100% Remote - Work From Home
• 🏝️ 80 hours PTO + vacation days
• Grow alongside a fast-growing US HealthTech AI company and help shape its future
• Hands-on ownership of production AI systems solving real healthcare problems
• The opportunity to work on AI products that move beyond prototypes and into real-world customer environments
• Direct collaboration with customers, engineering leaders, product teams, and company leadership
• Significant technical ownership and influence over how AI solutions are architected and deployed
• Long-term opportunity to become an integral member of a US-based engineering team