Lead Backend Engineer – AI Services

Harnham; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Harnham is seeking a Lead Backend Engineer - AI Services to build the backend foundation for AI capabilities and to productionize experiments within its SaaS analytics platform.

You will lead AI-oriented backend initiatives, shape architecture, and partner with Data Science to deploy AI pipelines, while ensuring reliability, security, and scalable performance across production systems.

Qualifications

• 15+ years of experience designing and implementing production SaaS applications.
• Strong backend engineering experience with Java.
• Experience designing scalable architectures for AI-enabled applications.
• Experience integrating machine learning and generative AI into commercial products.
• Experience with Linux production environments and CI/CD.

Responsibilities

• Develop and enhance backend services for a SaaS platform with emphasis on scalability and reliability.
• Lead AI-focused platform initiatives from problem definition through architecture and deployment.
• Collaborate with Data Science to productionize AI pipelines.
• Design reusable services and infrastructure for AI capabilities, including model serving and retrieval systems.
• Ensure security, monitoring, and maintainability in production systems.

Skills

Java

Python

FastAPI

MLflow

LangChain

LLM APIs

Vector databases

RAG

Model serving

AWS

Azure

GCP

SQL

CI/CD

Tools

MLflow

LangChain

RAG

LLM APIs

Vector databases

Feature stores

Model serving

Job description

About the Client

Our client is a privately held technology company that develops configurable SaaS analytics and workflow solutions for organizations that rely on data to improve decision-making, program oversight, and operational outcomes.

Their platform combines data, analytics, and workflow capabilities to help customers gain actionable insights, improve visibility, and make faster, more informed decisions. The company is continuing to evolve its SaaS platform and is investing in new AI capabilities that can be integrated into production products and customer-facing applications.

Our client is looking for a Lead Backend Engineer - AI Services to help build the backend foundation for these AI capabilities and take AI innovations from experimentation and proof of concept through production.

Role Overview

Our client is looking for an experienced backend engineer who can lead complex AI-focused engineering initiatives while helping establish reusable patterns and services for future AI development.

This is a hands-on technical leadership role that requires someone who can navigate ambiguity, independently drive complex initiatives, evaluate technical tradeoffs, and deliver scalable, reliable, and maintainable solutions.

The ideal candidate is an experienced software engineer who enjoys solving complex technical problems, building foundational platform capabilities, and transforming proof-of-concept ideas into production-ready customer solutions.

Key Responsibilities

• Develop and enhance backend services within a SaaS platform, with a focus on scalability, reliability, and maintainability.
• Lead complex AI-focused platform initiatives from problem definition through architecture, implementation, deployment, and operationalization.
• Break down ambiguous technical and business challenges into actionable work and drive solutions through completion.
• Partner closely with Data Science teams to transition proof-of-concept AI pipelines into scalable production services.
• Design and implement reusable services, integrations, and supporting infrastructure for AI capabilities, including model serving, LLM integration, orchestration, and retrieval services.
• Design systems that support rapid experimentation while maintaining the reliability, security, and operational standards required for production applications.
• Partner with Data Science to prototype new AI capabilities and evaluate emerging AI technologies, frameworks, and deployment approaches.
• Help shape backend architecture, engineering standards, reusable patterns, and foundational components for future platform development.
• Evaluate technical tradeoffs involving experimentation speed, scalability, reliability, security, maintainability, and long-term platform needs.
• Contribute to technical decisions involving build-versus-buy evaluations and emerging technologies.

Required Qualifications

• 15+ years of experience designing and implementing production SaaS applications, including modernizing and extending existing production platforms.
• Strong backend engineering experience with Java, including strong command of the language.
• Demonstrated experience designing and implementing scalable architectures for AI-enabled applications, including model deployment, APIs, data flows, integrations, and production operations.
• Demonstrated experience integrating machine learning and generative AI capabilities into commercial products or customer-facing applications.
• Experience working across both research/prototype and production environments.
• Working knowledge of Python, FastAPI, MLflow, LangChain or similar orchestration frameworks, vector databases, Retrieval-Augmented Generation (RAG), LLM APIs, model serving, feature stores, ML pipelines, prompt engineering, and agentic workflows.
• Experience with SQL and data-centric platform technologies.
• Experience implementing, enhancing, or maintaining business intelligence, analytics, or decision-support platforms.
• Strong software engineering fundamentals, including testing, CI/CD, monitoring, security, and source control.
• Experience deploying and supporting critical production systems in Linux environments.
• Experience working with or integrating systems deployed on AWS, Azure, or GCP.
• Strong technical judgment when evaluating architectural tradeoffs, emerging technologies, and build-versus-buy decisions.
• Strong debugging and problem-solving abilities, with an emphasis on taking ownership of problems from beginning to end.
• Experience partnering with Data Science teams to design and implement proof-of-concept infrastructure and pipelines supporting the experimentation lifecycle.
• Ability to work independently within a small team while managing multiple complex initiatives in a fast-paced environment.
• Comfortable working with and evolving an existing codebase rather than only building greenfield systems.
• Excellent organizational, documentation, and communication skills, including the ability to clearly explain technical challenges, evaluate options, communicate tradeoffs, and make recommendations to stakeholders.
• Must be a U.S. Citizen or Green Card holder.
• Ability to collaborate effectively with a geographically distributed team.

What You'll Work On

• AI-enabled backend services
• LLM and generative AI integrations
• RAG and retrieval systems
• Model serving and deployment
• AI orchestration and agentic workflows
• Data-centric platform technologies
• Productionizing AI and machine learning prototypes
• Modernizing and extending existing backend systems
• Architectural standards and reusable platform components

Why Consider This Opportunity?

This is an opportunity to play a foundational role in the development of AI capabilities within an established SaaS platform. The Lead Backend Engineer will have significant technical ownership and the opportunity to influence architecture, engineering practices, and how emerging AI technologies are translated into reliable production products.

The role offers the opportunity to work closely with experienced engineering and Data Science teams while solving complex problems at the intersection of backend engineering, data, and AI.