Forward Deployed AI Engineer, TechEx, Software -US

West Monroe•Washington, DC

12h•Hybrid

About The Position

At West Monroe, we believe the next generation of consulting will be built by small, highly capable teams that ship real software, solve hard problems, and create measurable value quickly. We are hiring a Forward Deployed AI Engineer—a hands-on software engineer who thrives in client environments and uses modern AI capabilities to enhance the systems they build. This role is fundamentally about engineering first: designing, building, and deploying production-grade software systems that improve how businesses operate. You will work directly with clients and cross-functional teams to deliver full-stack, data-driven, and AI-enabled solutions, moving from problem definition to production in fast-paced, high-impact environments. You will lead the design and development of production-ready software systems across infrastructure, integrations, data, and applications. You will be responsible for building systems that are reliable, scalable, and maintainable, while incorporating AI capabilities where they meaningfully improve outcomes. This role is best suited for engineers who want to stay close to the work—writing code, deploying systems, and solving real-world problems—while also shaping how solutions are delivered.

Requirements

5–8+ years of experience in software engineering, platform engineering, or related roles
Strong experience building and deploying production systems in cloud environments (AWS, Azure, GCP)
Solid foundation in computer science fundamentals (data structures, algorithms, system design)
Experience with API design, distributed systems, and system integration
Ability to operate autonomously in client-facing environments
Strong communication skills with both technical and non-technical stakeholders
Willingness to travel and embed with clients (25–50%)
Languages: Python, TypeScript/JavaScript, C#, Java, or similar
Frontend: React, Angular, or similar frameworks
Backend: API development, microservices, service-oriented architecture
Data: PostgreSQL, SQL Server, MongoDB, data pipelines
Cloud & DevOps: AWS/Azure/GCP, Docker, Kubernetes, Terraform, CI/CD pipelines
Integration Patterns: REST, GraphQL, event-driven systems
Experience integrating LLMs or AI capabilities into applications
Familiarity with prompt engineering, agent-based systems, or RAG pipelines
Experience using AI tools to enhance development workflows and automation

Nice To Haves

Experience with workflow orchestration tools (Temporal, Airflow, Inngest)
Familiarity with data platforms (Databricks, Snowflake)
Prior consulting or forward deployed engineering experience
Exposure to operationally complex industries (e.g., logistics, utilities, field services)

Responsibilities

Design, build, and deploy full-stack applications and distributed systems in client environments
Develop services, APIs, data pipelines, and user-facing applications that support core business operations
Integrate complex systems using REST APIs, webhooks, event-driven architectures, and custom connectors
Ensure systems are scalable, secure, and maintainable across cloud environments (AWS, Azure, GCP)
Incorporate AI/LLM capabilities into applications where they provide clear value (e.g., automation, decision support, user interfaces)
Build and deploy AI-powered features such as intelligent workflows, copilots, and agent-based systems
Develop prompting strategies and orchestration patterns to support production use cases
Leverage AI to improve engineering workflows, including testing, automation, and development acceleration
Work directly with clients to understand business needs and translate them into technical solutions
Move quickly from prototype to production, iterating based on user feedback
Communicate technical concepts clearly to both technical and non-technical stakeholders
Build platforms that unify fragmented data, workflows, and systems into usable applications
Design and implement workflow automations across systems and teams
Support production systems through monitoring, debugging, and continuous improvement
Write clean, maintainable, production-quality code
Contribute to reusable patterns, shared libraries, and platform capabilities
Operate in an Agile environment, balancing speed with long-term quality
Mentor team members and contribute to a strong engineering culture