Senior Agentic AI and Harness Engineer

HedgeServ Corporation; Województwo pomorskie; Hybrid; PLN 260,000 - 420,000; Full time

Benefits offered by this job

LuxMed Premium

Life & travel insurance

Employee Referral

Hybrid/Remote work opportunities

Education funding for ACCA/CIMA/IOB

Technical workshops

Job summary

HedgeServ Corporation is expanding its AI Engineering team to design, build, and operate production AI agents for financial operations and enterprise workflows. You will own the agent runtime, orchestration, controls, evaluation, and observability, with a focus on secure, auditable, and scalable solutions.

Bring strong software engineering, hands-on production LLM experience, and collaboration skills to establish reusable patterns across HedgeServ engineering teams.

Qualifications

• Bachelor’s degree in a technical field or equivalent practical experience.
• 5+ years of software engineering experience, with at least 1 year delivering LLM/agent-based production applications.
• Strong Python, API design, asynchronous processing, automated testing, source control, and AWS engineering skills; experience with Bedrock or equivalents.
• Hands-on experience implementing agent loops, context assembly, retrieval, memory, tool selection and limits, durable state, checkpoints, retries, and idempotency.
• Ability to build regression evaluations for outcomes, evidence, and tool paths; enforce least-privilege access and prompt-injection defenses.

Responsibilities

• Runtime: Design, deploy, and support reliable production runtimes for AI agents serving financial operations and enterprise workflows.
• Orchestration: Extend agent loops, including context assembly, retrieval, memory, tool selection, execution limits, workflow state, and response validation.
• Controls: Enforce authorization, human approvals, policy checks, validation, checkpoints, idempotency, retries, and exception handling.
• Enterprise integration: Build auditable tool and system interfaces with least-privilege permissions and defenses.
• Evaluation: Create regression tests for outcomes, evidence, and tool paths; diagnose quality, safety, latency, and cost.
• Observability: Monitor production agents, maintain audit evidence, and standardize engineering practices.

Skills

Python

API design

Asynchronous processing

Automated testing

Source control

AWS engineering

LLM/agent production

Troubleshooting

Cross-functional collaboration

Security and controls

Education

Bachelor’s degree in a relevant technical field or equivalent practical experience

Tools

Amazon Bedrock

Containers

CI/CD pipelines

Job description

The AI Engineering team builds secure, reliable, and reusable AI capabilities for HEDGESERV’s business and technology platforms, partnering across engineering, security, data, and operations to move solutions into production.

We integrate AI into existing workflows and platforms, focusing on measurable outcomes, production discipline, responsible AI, security, human oversight, and evidence-based evaluation.

Role Overview

You will design, build, and operate production AI agents for financial operations and enterprise workflows. In this role, the AI harness is the production layer around the model: the agent runtime, orchestration, controls, evaluation, and observability. You will own this layer, including retrieval, memory, tool execution, workflow state, human approvals, and safety controls.

You will bring strong software engineering skills, hands-on production LLM experience, sound architecture judgment, effective troubleshooting, and cross-functional collaboration. You will also establish reusable patterns for HEDGESERV engineering teams.

Key Responsibilities

• Runtime: Design, deploy, and support reliable production runtimes for AI agents serving financial operations and enterprise workflows.
• Orchestration: Build and extend agent loops, including context assembly, retrieval, memory, tool selection, execution limits, workflow state, and response validation.
• Controls: Enforce authorization, human approvals, policy checks, validation, checkpoints, idempotency, retries, and exception handling throughout agent workflows.
• Enterprise integration: Build validated, auditable tool and system interfaces with least-privilege permissions, prompt-injection defenses, and controls outside the model that isolate reasoning from deterministic execution.
• Evaluation: Build repeatable tests and regression suites for agent outcomes, supporting evidence, and tool-execution paths; diagnose quality, safety, failures, latency, and cost.
• Observability: Monitor and troubleshoot production agents, maintain audit evidence, and turn operational findings into reusable engineering standards.

Required Qualifications

• Bachelor’s degree in a relevant technical field or equivalent practical experience.
• 5+ years of software engineering experience, including at least 1 year delivering LLM or agent-based applications in production.
• Strong Python, API design, asynchronous processing, automated testing, source control, and AWS engineering skills; experience with a managed model platform such as Amazon Bedrock or an equivalent service.
• Hands-on experience implementing agent loops, context assembly, retrieval, memory, tool selection and limits, durable state, checkpoints, retries, and idempotency.
• Ability to build regression evaluations for outcomes, evidence, and tool paths; enforce least-privilege tool access and prompt-injection defenses; and separate model reasoning from deterministic controls.
• Strong troubleshooting, analytical, communication, and cross-functional collaboration skills.

Preferred Experience

• Experience in financial services or another regulated or highly controlled environment.
• Experience with model or tool gateways and interoperability protocols, such as MCP, plus multi-agent systems and durable workflow engines.
• Knowledge of secure tool execution, containers, infrastructure as code, CI/CD, and observability platforms.
• Familiarity with responsible AI, governance, model risk management, and regulatory controls.
• Experience building shared AI platforms, mentoring engineers, or establishing reusable engineering standards.
• Relevant certifications in AWS, cloud engineering, AI, security, or data.

We’re proud to offer a benefits package and workplace culture designed to support your health, career ambitions and life beyond work.

• LuxMed Premium Package
• Life insurance and travel insurance
• Employee Referral Program
• Remote/hybrid working opportunities, or from the office
• 100% funding for certifications and postgraduate studies accredited by ACCA, CIMA and IOB
• Technical workshops and soft skills training