AI Software Engineer

6257 - 8069 USD/ mies./ mies.B2BB2B (netto)

SeniorZdalnie·KrakówFull-time·B2B

#474561·Dodano dziś·0

Źródło: justjoin.it

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Tech Stack / Keywords

Java AWSRESTful APIsPython TypeScript JavaScript React Spring Boot

Podsumowanie oferty

Design and build agentic workflows and AI-powered products for enterprise customers in higher education. The role focuses on coordinating tools, services, data, and human approvals, and taking agentic capabilities from prototypes to production systems.

Wymagania

5+ years of experience in a software product development environment.
Strong proficiency with Java and Spring Boot.
Experience with JavaScript and React.
Experience with relational databases.
Hands-on experience building AI agents, tool-using LLM applications, or orchestrated workflows.
Experience using agents to support coding, code review, testing, release management, or incident response.
Senior-level experience building and operating production software systems.
Experience with TypeScript, Python, RESTful APIs, and infrastructure on AWS.
Experience with APIs, workflow engines, event-driven architectures, integrations, or distributed systems.
Strong understanding of testing, observability, security, permissions, and failure recovery.
Ability to turn ambiguous opportunities into practical, reliable technical solutions.
Strong communication skills and ability to influence engineering practices across a team.
Experience building enterprise SaaS or multi-tenant systems.
Leadership mindset and ability to drive changes across different teams.
Upper-intermediate English level.

Nice to have:

Experience with multi-agent systems, RAG, vector search, agent evaluation, or human-in-the-loop workflows.
Familiarity with higher education technology and its privacy and compliance requirements.
Experience leading technical transformation or introducing new engineering practices.

Obowiązki

Design and build agentic workflows that coordinate tools, services, data, and human approvals.
Develop reusable patterns for agent orchestration, tool use, context management, memory, and multi-agent collaboration.
Use agentic coding tools throughout planning, implementation, testing, debugging, refactoring, code review, and documentation.
Integrate agents into software development, testing, deployment, support, and operational workflows.
Establish standards for agent evaluation, observability, reliability, security, and governance.
Prototype new agentic capabilities and turn successful experiments into production systems.
Build complete, usable products rather than demonstrations or isolated model integrations.
Identify opportunities to improve engineering productivity and product delivery through agentic development.
Mentor engineers and help shape an agentic-first technical strategy across the organization.
Collaborate with product and engineering leaders to connect agentic capabilities to meaningful outcomes.
Use AI coding agents as engineering collaborators across an application codebase.
Provide agents with clear context, constraints, architecture, acceptance criteria, and technical direction.
Review, test, secure, and improve agent-generated code.
Decompose complex application work into agent-ready tasks while maintaining architectural consistency and product intent.
Create workflows in which agents can reason, select tools, call APIs, manage state, recover from failures, and escalate to people when appropriate.
Design agentic applications around user needs, including intuitive experiences, reliable workflows, permissions, audit trails, and error handling.
Move prototypes to production by addressing performance, scalability, security, monitoring, evaluation, cost, and ongoing maintenance.
Understand problems, make appropriate tradeoffs, and deliver complete solutions customers can depend on.

Benefity

Mentorship, TechTalks, and personalized growth roadmaps.
Budgets for education, fitness, and team activities.
Flexible schedule.

Elastyczne godziny

Dofinansowanie szkoleń

Inne informacje

Recruitment process: an online form, a 30–60-minute skills assessment, and a 5-minute introduction video, followed by a technical interview with the engineering team and a final interview with future teammates.

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