Senior Agentic Engineer

Project description

Modernization as a Service (MaaS) is a horizontal practice, supporting all business verticals in the company.

We are looking for a Senior Agentic Engineer who will be able to work with different modernization projects.

Responsibilities

• - Launch modernization toolset

  - Perform initial result validation

  - Customize and adjust prompts

  - Troubleshoot, debug, and resolve prompt issues

  - Collaborate with modernization team members to align with project goals and deliver high-quality solutions

SKILLS

Must have

• AI agents:
• Daily work with coding agents (Claude Code, Cursor, Codex or similar) as your main way of writing code, not an experiment.
• Understanding of how LLM agents work: context, tools, planning, subagents, typical failure modes.
• Ability to review agent output quickly and critically, catching errors and hallucinations.

  Engineering background:

• 5+ years of professional software development as a full stack developer, with systems taken to production and supported there.
• Relational databases and SQL; understanding of graph data models (Neo4j) and vector databases.
• Docker, Kubernetes, Helm: you deploy and debug them yourself.
• Testing as a habit: unit and integration tests, Testcontainers or similar.
• Understanding of TDD aspects.

  Soft skills:

• Owning an area on your own, from an unclear problem statement to production, without someone else breaking it into tasks.
• Willingness to make decisions with incomplete information and to own the outcome.
• Ability to get up to speed quickly in unfamiliar code, technology or business domains.
• Ability to explain a decision and its limits in writing and in person.

Nice to have

• Experience with LLM provider APIs (Anthropic, OpenAI, Bedrock) or a gateway such as LiteLLM.
• R&D experience: hypotheses, prototypes, experiments and data-driven decisions on problems with no known answer.
• Mainframe: COBOL, CICS, JCL, DB2, IMS, PL/I, HLASM, CA Gen, z/TPF; 3270 and z/OSMF.
• Experience building evals for non-deterministic systems: regression suites, metrics, comparison of models and prompts.
• Knowledge of threats to agents and the code they write: prompt injection, secret leakage, excessive permissions, poisoned dependencies and MCP servers (OWASP Top 10 for Agentic Applications).
• Secure work with coding agents.

Skills

AI agents:

• Daily work with coding agents (Claude Code, Cursor, Codex or similar) as your main way of writing code, not an experiment.
• Understanding of how LLM agents work: context, tools, planning, subagents, typical failure modes.
• Ability to review agent output quickly and critically, catching errors and hallucinations.

Engineering background:

• 5+ years of professional software development as a full stack developer, with systems taken to production and supported there.
• Relational databases and SQL; understanding of graph data models (Neo4j) and vector databases.
• Docker, Kubernetes, Helm: you deploy and debug them yourself.
• Testing as a habit: unit and integration tests, Testcontainers or similar.
• Understanding of TDD aspects.

Soft skills:

• Owning an area on your own, from an unclear problem statement to production, without someone else breaking it into tasks.
• Willingness to make decisions with incomplete information and to own the outcome.
• Ability to get up to speed quickly in unfamiliar code, technology or business domains.
• Ability to explain a decision and its limits in writing and in person.

Experience

AI agents:

• Daily work with coding agents (Claude Code, Cursor, Codex or similar) as your main way of writing code, not an experiment.
• Understanding of how LLM agents work: context, tools, planning, subagents, typical failure modes.
• Ability to review agent output quickly and critically, catching errors and hallucinations.

Engineering background:

• 5+ years of professional software development as a full stack developer, with systems taken to production and supported there.
• Relational databases and SQL; understanding of graph data models (Neo4j) and vector databases.
• Docker, Kubernetes, Helm: you deploy and debug them yourself.
• Testing as a habit: unit and integration tests, Testcontainers or similar.
• Understanding of TDD aspects.

Soft skills:

• Owning an area on your own, from an unclear problem statement to production, without someone else breaking it into tasks.
• Willingness to make decisions with incomplete information and to own the outcome.
• Ability to get up to speed quickly in unfamiliar code, technology or business domains.
• Ability to explain a decision and its limits in writing and in person.
• Experience with LLM provider APIs (Anthropic, OpenAI, Bedrock) or a gateway such as LiteLLM.
• R&D experience: hypotheses, prototypes, experiments and data-driven decisions on problems with no known answer.
• Mainframe: COBOL, CICS, JCL, DB2, IMS, PL/I, HLASM, CA Gen, z/TPF; 3270 and z/OSMF.
• Experience building evals for non-deterministic systems: regression suites, metrics, comparison of models and prompts.
• Knowledge of threats to agents and the code they write: prompt injection, secret leakage, excessive permissions, poisoned dependencies and MCP servers (OWASP Top 10 for Agentic Applications).
• Secure work with coding agents.