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

  • 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

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Hiring process timeline

We designed our hiring process to be fast, transparent, and convenient — so you always know what to expect and can move through the steps without unnecessary delays.

lightning-iconA quick note

After applying, keep an eye on your inbox — including your spam folder. Occasionally, emails from our hiring platform, LaunchPod, may land there.

1

Tell us about yourself

Submit a short application form.

2

Pass a quick test

Pass a 30’- 60’ test.

3

Record a short video

Introduce yourself on video to fast-track your application process.

4

Meet our team

Once you pass the video review, grab a spot on our calendar for a technical interview.

5

Get an offer

Welcome to AgileEngine!

FAQ

Have any questions?

What is the work format and schedule?

We are a remote-first company, so all our positions are remote. Schedules are flexible, but the main requirement is to have an overlap with your client’s schedule to ensure smooth collaboration. Specific details depend on the project and are discussed during the interview process.

What level of English is required?

We look for Upper-Intermediate (B2) proficiency or higher. Since you will be collaborating with international teams and global clients (including Fortune 500 companies), English is a part of your daily work.

Does AgileEngine provide work equipment?

It depends on your location. We provide equipment in Ukraine, Poland, Argentina, Colombia, Mexico, Brazil, Guatemala, Portugal, Spain, and India. In the USA, equipment is usually provided by the client; otherwise, you will be expected to use your own setup.

What opportunities for professional growth do you offer?

We support continuous growth through personalized development paths tailored to each expert. Also, you can expect:

  • An annual learning and development budget
  • Internal workshops, tech talks, and mentorship programs
  • Opportunities to switch projects or grow into new roles over time

What does a typical team look like, and what tools do you use?

Teams vary by project, but you’ll usually work with a mix of experts across different fields, along with a delivery or project manager who supports collaboration and onboarding.

For day-to-day work, teams commonly use tools like Jira and Google Workspace, along with communication platforms such as Google Chat. Depending on the client, you may also work with Slack, Confluence, Notion, or similar tools.

Need help?

Want more details? See full FAQ

If something doesn’t work or you have questions regarding your application process, drop us a line.

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