Lead AI engineer

Grid Dynamics; Wrocław; On-site; PLN 300,000 - 600,000; Full time

Benefits offered by this job

Medical insurance

Sports benefits

Corporate events

Professional development

Well-equipped office

Job summary

Grid Dynamics seeks a Lead AI Software Engineer to own the technical direction and architecture of a next-generation enterprise AI platform. You will oversee distributed systems, security, and multi-tenant cloud deployments across AWS, Azure, and GCP, guiding an engineering team and partnering with Forward Deployment teams.

You will write Python, work with LangGraph/Tooling, and drive architecture decisions for cost, latency, and compliance while ensuring robust installations in customer clouds.

Qualifications

• 8+ years of commercial software engineering experience in tech lead roles.
• Shipping and operating LLM-based applications at scale and defending against prompt-injections.
• Deep multi-tenant SaaS architecture and cloud deployment across AWS/Azure/GCP.

Responsibilities

• Lead and mentor a team of senior engineers and set technical standards.
• Own end-to-end platform architecture for enterprise AI platform.
• Design data isolation, identity, and access for single-tenant/cloud installs and multi-tenant offerings.
• Lead hands-on engineering on distributed systems, performance under load, and security.
• Collaborate with product leadership to translate roadmaps into engineering commitments.

Skills

Leadership

Architectural design

Distributed systems

Python

TypeScript/Node.js

PostgreSQL

Cloud (AWS)

Tools

LangGraph

Cerbos

WorkOS

Job description

We are seeking a Lead AI Software Engineer to own the technical direction and architecture of a next-generation, enterprise-grade agentic AI platform for a leading global fintech company. Delivered as a single-tenant deployment into each customers' cloud environment, every architectural decision behind the platform must scale seamlessly across AWS, Azure, and GCP- operating securely behind enterprise identity providers and on sensitive financial data. In this pivotal technical leadership role, you will guide the engineering team, set the overall platform architecture, lead complex distributed systems engineering hands-on, and partner closely with Forward Deployment teams to ensure flawless installation, execution, and isolation across diverse customer clouds.

Responsibilities

• Engineering Leadership: Lead and mentor a team of senior engineers, establishing technical standards, conducting thorough code reviews, and fostering a culture of engineering excellence across the squad.
• Platform Architecture: Own the end-to-end architecture of the enterprise AI platform- agent orchestration (LangGraph), tool execution, memory, retrieval (RAG), observability, identity, and authorization. Author Architecture Decision Records (ADRs) and make key decisions regarding data models, async patterns, caching, and deployment topologies.
• Multi-Tenant & Cloud Foundations: Design robust data isolation, identity, and access management for single-tenant customer-cloud installs, ensuring seamless scaling to managed multi-tenant offerings. Architect integrations with multi-tenant SSO brokers (WorkOS) and policy decision engines (Cerbos).
• LLM & Agent Safety: Architect enterprise guardrails, prompt-injection defenses, PII redaction, and output validation pipelines. Drive cost discipline, model routing, token budgeting, and caching strategies while making agent decisions fully auditable, traceable, and defensible to client CISOs.
• Hands-On Engineering & Delivery: Personally lead the most challenging technical work - distributed systems edge cases, performance investigations under load, online migrations, and security architecture. Write high-quality Python code and partner with Product leadership to translate roadmaps into coherent, on-time engineering commitments.
• Stakeholder & Client Alignment: Serve as the primary technical authority in customer discussions, CISO security reviews, and architecture deep-dives, partnering with Forward Deployment leads on deployment topologies.

Requirements

• Technical Leadership Scope: 8+ years of commercial software engineering experience, with a proven track record in a Tech Lead, Team Lead, or Principal Engineer capacity leading complex distributed systems or AI projects.
• Production LLM Systems: Proven experience shipping and operating LLM-based applications at scale - expert-level prompt engineering, advanced RAG, tool-using agent frameworks (LangGraph), prompt-injection defense, evaluation pipelines, and cost/latency management.
• Multi-Tenant Architecture: Deep expertise in shipping multi-tenant products, with a strong understanding of trade-offs across shared-everything, shared-database, and isolated single-tenant/silo deployments.
• Distributed Systems & Security: Strong foundation in distributed systems (idempotency, eventual consistency, queue-based async, distributed locking) and security architecture (end-to-end authn/authz, OWASP mitigation, RBAC/ABAC).
• Core Tech Stack: Advanced proficiency in Python (with working knowledge of TypeScript/Node.js) and strong PostgreSQL expertise under heavy load (pool tuning, indexing, online migrations, and pgvector/vector stores).
• Cloud-Native Architecture: Strong expertise in AWS, with a working knowledge of Azure or GCP, focusing on portable, multi-cloud deployment topologies.
• Exceptional team leadership, mentoring abilities, and written/verbal English communication skills to engage seamlessly with cross-functional partners and senior executive stakeholders.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.