The Role
Build production-grade AI applications, agents, backend services, and MCP integrations using Java and/or Python. Design agentic workflows, prompt orchestration, context management, tool calling, memory, and evaluation systems. Integrate LLMs with enterprise tools while balancing reliability, performance, cost, and safety. Collaborate across engineering and product teams, investigate production issues, improve observability, support releases, resolve incidents, and document AI engineering best practices.
Summary Generated by Built In
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Senior AI Engineer to build AI-powered applications, agents, and MCP integrations connecting intelligent systems to business tools. Working in Java and/or Python, this person turns LLM capabilities into production-grade backend services, balancing performance, reliability, and cost. Comfort moving between experimentation and production support matters here.
WHAT YOU WILL DO
- Design, build, and enhance AI-powered applications and backend services for internal or customer-facing use cases.
- Build and maintain AI agents and agentic workflows that can reason, orchestrate tasks, and integrate with enterprise tools and services.
- Develop MCP-based integrations and tool interfaces that enable AI systems to interact securely with external platforms, APIs, and business systems.
- Implement prompt orchestration, context handling, tool calling, memory patterns, and evaluation workflows for reliable agent behavior.
- Collaborate with engineering, product, and architecture teams to define scalable patterns for AI agent development and deployment.
- Integrate LLM capabilities into software systems while balancing performance, reliability, cost, and safety.
- Investigate system issues, improve quality and observability, and optimize AI workflow efficiency in production environments.
- Participate in code reviews, release support, experimentation, and production incident resolution.
- Create technical documentation and contribute to best practices for AI engineering, agent development, and MCP adoption.
MUST HAVES
- 4+ years of experience in software engineering, backend engineering, or applied AI engineering.
- Strong programming skills in Java and/or Python.
- Hands-on experience building AI-powered applications or integrating LLM capabilities into production systems.
- Experience designing or building AI agents, multi-step orchestration workflows, or tool-using automation systems.
- Experience with MCP or similar integration patterns for connecting AI systems to external tools, APIs, or enterprise platforms.
- Strong understanding of system design, APIs, distributed systems, and production software engineering fundamentals.
- Familiarity with prompt design, context management, evaluation approaches, and reliability patterns for agent-based systems.
- Proven ability to work effectively in fast-paced delivery environments.
- Delivery-oriented and comfortable operating across development, experimentation, and production support responsibilities.
- Effective at collaborating with cross-functional teams under tight timelines.
- Strong ownership mindset with practical problem-solving skills.
- Upper-intermediate English level.
NICE TO HAVES
- Experience with multi-agent systems, retrieval-augmented generation, semantic search, or vector-based architectures.
- Familiarity with cloud-native infrastructure, monitoring, and observability for AI services.
- Experience with model evaluation, guardrails, safety patterns, and prompt/version lifecycle management.
- Experience integrating AI solutions with enterprise platforms such as Salesforce, Jira, Slack, or internal developer tools.
- Background in workflow automation, event-driven systems, or backend platforms that support AI-enabled products.
PERKS AND BENEFITS
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
Skills Required
- 4+ years of experience in software engineering, backend engineering, or applied AI engineering
- Strong programming skills in Java and/or Python
- Hands-on experience building AI-powered applications or integrating LLM capabilities into production systems
- Experience designing or building AI agents, multi-step orchestration workflows, or tool-using automation systems
- Experience with MCP or similar integration patterns connecting AI systems to external tools, APIs, or enterprise platforms
- Strong understanding of system design, APIs, distributed systems, and production software engineering fundamentals
- Familiarity with prompt design, context management, evaluation approaches, and reliability patterns for agent-based systems
- Ability to work effectively in fast-paced delivery environments
- Comfort operating across development, experimentation, and production support responsibilities
- Ability to collaborate with cross-functional teams under tight timelines
- Strong ownership mindset and practical problem-solving skills
- Upper-intermediate English level
- Experience with multi-agent systems, retrieval-augmented generation, semantic search, or vector-based architectures
- Familiarity with cloud-native infrastructure, monitoring, and observability for AI services
- Experience with model evaluation, guardrails, safety patterns, and prompt/version lifecycle management
- Experience integrating AI solutions with enterprise platforms such as Salesforce, Jira, Slack, or internal developer tools
- Background in workflow automation, event-driven systems, or backend platforms supporting AI-enabled products
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The Company
What We Do
AgileEngine is a privately held company established in 2010 that builds dedicated teams of designers and developers. We turn good ideas into awesome software that people actually want to use. Some of the biggest names and the hottest startups around the world chose us to build their tech.
