Senior Agentic AI Engineer

• Remote working

• Comprehensive premium health insurance

• Sports club membership

• My Benefit – cafeteria system access

• Competitive compensation package

• Support for tuition and continued education

• Active sports and social events committee

• Design, develop, and maintain production-grade AI agent architectures and execution frameworks.

• Build agent orchestration mechanisms covering task planning, context management, retrieval, memory, and tool interaction.

• Develop reliable workflows incorporating state persistence, checkpointing, retry strategies, error recovery, and execution safeguards.

• Integrate LLM-based solutions with internal applications, APIs, databases, and enterprise services.

• Implement security and governance mechanisms, including access controls, approval workflows, input validation, and protection against prompt injection.

• Ensure appropriate separation between AI-driven decision-making and deterministic business logic.

• Create automated testing and evaluation frameworks to assess agent accuracy, reliability, tool usage, and overall performance.

• Establish monitoring and observability capabilities to track system behavior, execution quality, latency, and operational costs.

• Identify opportunities to improve agent performance, scalability, and maintainability.

• Collaborate with cross-functional teams to deliver AI solutions from initial design through production deployment.

• Contribute to architectural decisions, technical documentation, and engineering best practices.

We are looking for an experienced Senior Agentic AI & Harness Engineer to join a technology-driven organization developing advanced AI solutions for complex enterprise environments.

The role focuses on building scalable, secure, and production-ready AI agent systems that automate business processes, integrate with enterprise applications, and support operational decision-making.

You will play a key role in designing the infrastructure and engineering frameworks that enable AI agents to operate reliably in real-world environments. Working closely with software engineering, data, cloud, and security teams, you will help establish technical standards and reusable solutions for enterprise AI adoption.

• At least 5 years of professional software engineering experience, including hands-on experience delivering LLM-powered or agent-based solutions in production.
• Advanced Python programming skills and strong knowledge of modern software engineering practices.
• Practical experience developing AI agents, orchestration frameworks, and LLM-based applications.
• Solid understanding of retrieval-augmented generation (RAG), context engineering, memory management, and tool-calling mechanisms.
• Experience implementing asynchronous processing, API integrations, stateful workflows, and fault-tolerant systems.
• Strong knowledge of AWS cloud services and experience working with managed LLM platforms such as Amazon Bedrock or similar technologies.
• Experience designing automated tests, evaluation pipelines, and regression testing for AI-powered applications.
• Understanding of application security, authorization mechanisms, and secure integration patterns.
• Familiarity with CI/CD pipelines, version control, and production deployment practices.
• Strong problem-solving skills and the ability to troubleshoot complex distributed systems.
• Good communication skills and experience collaborating with multidisciplinary engineering teams.

Nice to have:

• Experience working in financial technology, enterprise software, or regulated industries.
• Knowledge of Model Context Protocol (MCP), model gateways, and advanced tool integration architectures.
• Experience with multi-agent frameworks and workflow orchestration technologies.
• Familiarity with containerization, infrastructure as code, and cloud-native architectures.
• Knowledge of AI governance, responsible AI practices, and model risk management.
• Experience building internal AI platforms, shared engineering libraries, or reusable development frameworks.
• Relevant cloud, AI, or security certifications.
• Experience providing technical guidance or mentoring other engineers.

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