Agentic AI Software Engineer

Harnham; Houston (TX); Hybrid; USD 162,000 - 198,000; Full time

Benefits offered by this job

Hybrid work model

Relocation package

On-site 4 days a week

Job summary

Harnham seeks an Agentic AI Software Engineer to design, build, and deploy production-grade AI agents within enterprise workflows. You will own agent architecture, orchestration, and memory management while integrating with APIs, databases, and business systems.

You should have 6+ years in software engineering and 3+ years building AI agents in production, with strong frontend and backend skills and experience with React, Next.js, Python, and cloud deployments.

Qualifications

• Bachelor's degree in CS, SE, Information Systems or related discipline.
• 6+ years of combined software engineering and AI development experience.
• Proven experience building AI agents, agentic workflows, or production LLM applications.
• Experience with React, Angular, Next.js, or similar frameworks.
• Strong Python development experience and cloud-based deployments.

Responsibilities

• Design and build AI agents capable of reasoning through complex business workflows.
• Develop support agents that understand user intent, maintain context, retrieve information, and take actions.
• Create multi-step agentic workflows leveraging LLMs, APIs, business logic, enterprise systems, and knowledge sources.
• Design memory, context, retrieval, and personalization frameworks.
• Implement guardrails, evaluation methodologies, fallback mechanisms, and a human-in-the-loop process.
• Optimize agent performance across accuracy, latency, reliability, cost, and task completion metrics.

Skills

Full-stack development

AI agent development

Frontend development

Backend development

API integration

Education

Bachelor's degree in Computer Science or related

Tools

React

Next.js

Angular

Python

FastAPI

Flask

Django

Job description

Agentic AI Software Engineer

Overview

We're partnering with an organisation investing heavily in AI-driven products and intelligent automation. This position is ideal for a software engineer who began their career in full-stack development and has since specialised in designing, building, and deploying AI agents in production environments. This is not an AI-assisted coding role. We are seeking someone who has personally built and deployed AI agents, agent orchestration frameworks, and agentic workflows that interact with enterprise systems, APIs, and business processes. The successful candidate will become the primary builder of AI agents within a growing AI engineering function, delivering high-value initiatives and shaping the future of enterprise AI capabilities.

Compensation, Location & Logistics

• Salary: Up to $180,000
• Bonus: Up to 15% annual bonus
• Relocation Assistance: $10,000 relocation package available
• Work Model: Hybrid
• Location: Houston, TX
• Office Requirement: 4 days per week on-site
• Remote Flexibility: Candidates outside a 50-mile radius may be eligible for a reduced on-site requirement of approximately 4 days per month
• Sponsorship: Not available

Interview Process

• Initial recruiter screening
• Online technical assessment
  • Coding evaluation
  • LLM and AI fundamentals assessment
• Technical interview with AI Engineering leadership
  • Deep dive into agent architecture, product delivery, and real-world use cases
• Final on-site panel interview with technical and business stakeholders

What We're Looking For

Essential Background

• Minimum 3+ years of full-stack software engineering experience
• Minimum 3+ years of hands-on AI agent development experience
• Strong track record building and deploying production-grade AI agents
• Experience designing agentic workflows beyond prompt engineering or AI coding assistants
• Deep understanding of:
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Agent orchestration
  • Tool calling
  • Agent memory and context systems
  • AI evaluation and monitoring frameworks
• Strong frontend and backend development expertise
• Experience integrating AI systems with APIs, databases, enterprise applications, and external services

Ideal Candidate Profile

You likely started your career as a software engineer and evolved into AI engineering, spending recent years focused on designing, building, and operating intelligent agents in production rather than simply consuming AI tools. You understand how to architect systems where AI can reason, retrieve information, interact with tools, and complete business workflows safely and effectively.

Key Responsibilities

Agentic AI Development

• Design and build AI agents capable of reasoning through complex business workflows
• Develop support agents that can understand user intent, maintain context, retrieve information, and take meaningful actions
• Create multi-step agentic workflows leveraging LLMs, APIs, business logic, enterprise systems, and knowledge sources
• Design memory, context, retrieval, and personalisation frameworks
• Implement guardrails, evaluation methodologies, fallback mechanisms, and human-in-the-loop processes
• Optimise agent performance across accuracy, latency, reliability, cost, and task completion metrics

Full-Stack Product Development

• Build user-facing applications that enable interaction with AI-powered experiences
• Develop modern frontend applications using frameworks such as React, Next.js, or Angular
• Build backend services and APIs using Python frameworks including FastAPI, Flask, or Django
• Own solutions end-to-end from architecture through deployment
• Ensure scalability, security, reliability, and maintainability of AI-enabled products

RAG, Data & AI Infrastructure

• Develop RAG pipelines that connect agents to structured and unstructured enterprise knowledge
• Build data ingestion and integration pipelines
• Connect AI systems to APIs, databases, workflow engines, and business applicationsHelp establish infrastructure supporting agent memory, retrieval, and contextual reasoning
• Maintain high standards for security, reliability, and performance

LLM Engineering

• Integrate and orchestrate leading AI models within production environments
• Develop prompting, retrieval, context management, and tool-selection strategies
• Build conversational AI, intelligent search, document processing, and workflow automation capabilities
• Evaluate model performance, architectures, providers, and costs
• Create monitoring and evaluation frameworks to measure business impact and technical effectiveness

Engineering Excellence

• Implement CI/CD, testing, observability, and monitoring practices
• Establish best practices around software quality, documentation, security, and deployment
• Leverage modern AI engineering tools while maintaining strong engineering discipline
• Stay current with emerging agent frameworks, AI tooling, and industry best practices

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related discipline
• 6+ years of combined software engineering and AI development experience
• Strong full-stack development experience across frontend and backend technologies
• Experience building scalable APIs and distributed applications
• Proven experience building AI agents, agentic workflows, or production LLM applications
• Experience with:
  • LLMs
  • RAG architectures
  • Tool calling
  • Agent orchestration frameworks
  • AI evaluation methodologies
• Experience developing applications using React, Angular, Next.js, or similar frameworks
• Strong Python development experience
• Experience working with cloud-based environments and modern deployment practices
• Experience using AI-enabled development tools responsibly and effectively

Preferred Qualifications

• Experience with Databricks or modern lakehouse platforms
• Experience with GCP or similar cloud environments
• Infrastructure-as-code and DevOps experience
• Experience building enterprise-scale AI products
• Background working within cross-functional Agile teams

What Success Looks Like

• Build and deploy production-ready AI agents that drive measurable business outcomes
• Become the team's go-to technical expert for agent architecture and orchestration
• Deliver reliable, scalable, and secure AI solutions in enterprise environments
• Help define AI engineering best practices and agent development standards across the organisation