Forward Deployed Engineer

Role Summary

As a Forward Deployed Engineer you will embed directly with airline business and operations teams to identify high-value problems and rapidly build, deploy and scale AI-powered solutions on AWS. You sit at the intersection of engineering, product and the customer: you discover the problem onsite, prototype quickly with GenAI and agentic technologies (Amazon Bedrock, AgentCore, MCP), and own the path to a secure, production-grade solution that moves operational and customer metrics.

Key Responsibilities

Work onsite with stakeholders across flight operations, crew, TechOps/maintenance, airports, customer service and corporate functions to discover and prioritize AI use cases

Translate ambiguous business problems into technical designs, working prototypes and production deployments, often within weeks

Design and build GenAI and agentic solutions using Amazon Bedrock, AgentCore and frameworks such as LangGraph / LangChain / Strands Agents

Build MCP-based integrations and APIs that connect AI agents to airline systems of record, operational data and enterprise tools

Implement RAG pipelines over manuals, policies, maintenance records and operational data; tune retrieval quality

Establish evaluation, guardrails and observability for LLM workloads; optimize latency, accuracy and cost

Deliver using IaC (Terraform / CloudFormation / CDK), CI/CD and serverless / containerized patterns aligned with enterprise standards

Partner with AI Architects and AI Engineers: feed field learnings back into reusable components, patterns and platform roadmap

Present solutions, demos and outcomes to technical teams and business leadership; drive user adoption and iteration

Ensure solutions meet security, privacy (PII) and regulatory requirements of the airline environment

Required Qualifications

5+ years hands-on software engineering, delivering production applications on AWS Cloud

Airline industry experience: delivered technology solutions in an airline environment (flight ops, crew scheduling, TechOps/MRO, airport ops, revenue management, customer service / loyalty)

Forward-deployed / customer-facing engineering: embedded with business & operations teams onsite, turning ambiguous problems into shipped solutions

Strong programming in Python plus one of Java, TypeScript or Node.js (back-end depth is MUST, full-stack ability expected)

Built and shipped GenAI / LLM solutions to production (beyond POCs) with measurable business outcomes

Hands-on with AWS AI services, specially Bedrock / AgentCore (personally built, not only evaluated)

Agentic frameworks in production (LangChain, LangGraph, Strands Agents or similar)

MCP-based integrations connecting AI agents with enterprise tools, APIs and data

RAG pipelines: chunking, embeddings, vector stores (OpenSearch, pgvector or similar), retrieval tuning

Prompt engineering and LLM evaluation (eval datasets, guardrails, hallucination & regression testing)

Proficiency in AWS core services (S3, Lambda, API Gateway, RDS/DynamoDB, Step Functions, EventBridge)

Serverless & microservices architecture; containerization (Docker, Kubernetes / ROSA)

Integrating with legacy / enterprise systems of record (REST/SOAP APIs, messaging, batch & streaming data)

Infrastructure as Code (Terraform, CloudFormation or CDK) and CI/CD pipelines & DevOps practices

Experience using AI-assisted dev tools, preferably Kiro, for coding/testing/docs/debugging

Rapid prototyping: demo-able MVP in days/weeks, then hardening it for production (scalability, reliability)

Observability, latency and cost optimization of LLM workloads (CloudWatch, tracing, token/cost tracking)

Application security, IAM and data privacy for AI solutions (PII handling, least privilege, responsible AI)

Requirements discovery and communication: whiteboarding with users, presenting to technical and executive audiences

Strong ownership and problem-solving in fast-paced, ambiguous environments

Preferred Qualifications

Bachelor's degree in CS, IS, Engineering or related field

Familiarity with airline systems & standards (PSS such as Amadeus/Sabre, NDC, IATA messaging, ACARS)

AWS certifications (Solutions Architect, Developer, Machine Learning / GenAI related)

Multi-agent orchestration patterns, model fine-tuning or SageMaker experience

Front-end skills (React or similar) for quick user-facing tools and demos

Experience in regulated environments (FAA, DOT, TSA, PCI-DSS)