AI Software Engineer

Mindlance

Ann Arbor, MI

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JOB DETAILS

SKILLS

Agile Programming Methodologies, Amazon Web Services (AWS), Application Programming Interface (API), Architectural Services, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Benchmarking, Best Practices, Cloud Computing, Coding Standards, Computer Programming, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Customer Experience, Data Science, Design Patterns Programming Methodologies, Docker, Enterprise Applications, GCP (Good Clinical Practices), Git, High Reliability, Identify Issues, Identity Data Management, Information Retrieval, Java, JavaScript, MCP - Microsoft Certified Professional, Machine Learning, Microservices, Microsoft C# (C Sharp), Microsoft Windows Azure, Modeling Languages, Object Oriented Design (OOD), Performance Modeling, Performance Tuning/Optimization, Privacy Controls, Production Support, Production Systems, Python Programming/Scripting Language, REST (Representational State Transfer), Requirements Management, Scalable System Development, Semantic Search, Software Administration, Software Development, Software Engineering, Source Code/Configuration Management (SCM), Test Automation, Test Plan/Schedule

LOCATION

Ann Arbor, MI

POSTED

8 days ago

Work Location: Ann Arbor, MI

6 months 100% onsite and then after the 6 months 4 days onsite and 5th remote. Candidate is able to pick their remote day.

Mid-Level AI Engineer / AI Developer
Position Summary
We are seeking a Mid-Level AI Engineer to design, develop, and deploy AI-powered applications and services. This role will work closely with software engineers, product managers, architects, and data teams to build scalable AI solutions using modern machine learning, generative AI, agent frameworks, and enterprise software engineering practices.
The ideal candidate combines strong software development skills with hands-on experience building, integrating, and operating AI solutions in production environments.
Key Responsibilities

Design, develop, test, and deploy AI-enabled applications and services.
Build and integrate Generative AI solutions using large language models (LLMs).
Develop AI agents, workflows, prompts, tools, and orchestration frameworks.
Implement retrieval-augmented generation (RAG), semantic search, and knowledge retrieval solutions.
Build APIs, microservices, and backend services supporting AI workloads.
Evaluate, benchmark, and optimize AI model performance, quality, cost, and latency.
Develop automated testing, monitoring, and observability for AI applications.
Collaborate with product owners and business stakeholders to translate requirements into technical solutions.
Implement responsible AI, security, privacy, and governance controls within AI solutions.
Contribute to architectural decisions, coding standards, and engineering best practices.
Support AI applications in production and participate in troubleshooting and incident resolution.

Required Qualifications

Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field.
3–6 years of software development experience.
2+ years of experience building AI/ML or Generative AI applications.
Strong programming skills in one or more of:

o Python
o Java
o C#
o TypeScript/JavaScript

Experience developing REST APIs and distributed services.
Experience working with cloud platforms such as:

o Azure
o AWS
o GCP

Strong understanding of software engineering fundamentals:

o Design patterns
o Testing
o CI/CD
o Security
o Observability

Preferred Qualifications

Experience with LLM platforms such as:

o OpenAI
o Anthropic Claude
o Azure OpenAI
o Gemini

Experience building:

o AI agents
o MCP-based integrations
o Tool calling frameworks
o Multi-agent workflows

Experience with RAG architectures and vector databases.
Familiarity with prompt engineering and evaluation frameworks.
Experience with containerization and orchestration:

o Docker
o Kubernetes
o Cloud Run

Experience working in Agile development environments.

Technical Skills

AI / Machine Learning
Generative AI
Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Embeddings and Vector Search
AI Agent Frameworks
Model Evaluation and Benchmarking

Software Engineering

Object-Oriented Design
API Design
Microservices
Event-Driven Architecture
Automated Testing
CI/CD Pipelines
Git and Source Control

Cloud & Infrastructure

Azure, AWS, or GCP
Containers and Kubernetes
Monitoring and Observability
Identity and Access Management
Secure Deployment Practices

Success Measures

Delivers production-ready AI features with high quality and reliability.
Improves developer and customer productivity through AI-enabled capabilities.
Builds scalable and secure AI services aligned with enterprise governance requirements.
Demonstrates ownership from design through deployment and production support.
Collaborates effectively across engineering, architecture, product, and business teams.

Typical Projects

AI assistants and copilots
MCP servers and AI integrations
Knowledge search and RAG platforms
Agentic workflows and automation
Document intelligence solutions
AI-powered developer productivity tools
Conversational client experiences

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”

About the Company

Mindlance

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