Role Description Join Liftoff as a GenAI Software Engineer and shape the future of ad tech. This role sits within the Creative GenAI (CGenAI) team and is dedicated to advancing the strategic initiatives that define how Liftoff applies generative AI to creative. Reporting to the Senior Director, Creative GenAI, you'll build intelligent agents to optimize workflows, and architect AI-powered solutions that transform how our business operates by leveraging cutting-edge vision and diffusion models to revolutionize creative production. In this role, you'll have an immediate impact on our AI strategy and product development. We foster a collaborative environment where you'll work closely with key decision makers to bring innovative solutions to life. You'll have the freedom to experiment, mentor others, and grow into a thought leader who defines not just Liftoff's AI future, but influences the broader ad tech industry. This role is ideal for an engineer who thrives in ambiguity, has a passion for experimentation, and wants to push the boundaries of what's possible with LLMs. You'll have the opportunity to tackle complex challenges, validate new approaches, and drive meaningful improvements across our organization. What You'll Do - Architect and ship AI systems that generate ad creatives end-to-end - including interactive playables - combining code generation, multimodal asset generation, and runtime quality into production-grade pipelines. - Rapidly prototype against real creative problems, then take what works from proof-of-concept to production at speed. - Partner closely with creative strategists, content leads, and builders to translate craft expertise into systems that scale. - Design robust systems that handle the inherent variability of AI-generated output through thoughtful guardrails, fallbacks, and quality gates. - Build evaluation infrastructure tailored to creative output, spanning subjective quality assessment, human-in-the-loop review, and A/B testing against real ad performance. - Drive innovation by researching new model capabilities and proposing new initiatives as the frontier moves. - Mentor the team and raise the bar on engineering practices, fostering an environment of open feedback and shared learning. Qualifications - Minimum Bachelor's Degree and 5 years of relevant experience. - Senior engineer with significant pre-LLM production experience and solid fundamentals in system design, debugging, and observability. - Strong in Python for AI/agent work and fluent in JavaScript/TypeScript for creative and playables work; HTML and gaming experience a plus. - Has shipped LLM-powered systems to production, learned the failure modes firsthand, and makes deliberate choices about what the model handles versus what belongs in code, tools, or context. - Treats evaluations as first-class infrastructure and has built autonomous agents with a realistic sense of what today's multimodal models can and can't do. - Clear communicator who collaborates well across teams and disciplines, navigating ambiguity and adapting as priorities shift. Requirements - Travel Expectations: We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. Benefits - Liftoff offers all employees a full compensation package that includes equity and health/vision/dental benefits associated with your country of residence. - Base compensation will vary based on the candidate's location and experience. - Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. - Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence.

• Architect multi-cloud AI solutions leveraging Azure AI, Azure OpenAI, AWS Bedrock, serverless components, microservices, and AI agents • Design end-to-end AI-enabled IAM workflows integrating identity data, LLMs, RAG pipelines, vector databases, and IAM toolchains • Lead Python-based microservices development (FastAPI/Flask) for IAM automation and API-driven integrations • Design AI orchestration using LangChain, LangGraph, AutoGen, LlamaIndex, and Semantic Kernel • Build autonomous multi-agent systems with reasoning and decision intelligence • Lead client workshops, PoCs, MVPs, and presales demonstrations

• Architect secure agent-based AI systems including multi-agent orchestration and RAG pipelines • Design and deploy agentic workflows using LangChain, LangGraph, AutoGen and MCP • Build autonomous reasoning, planning and tool-using AI agents • Integrate LLMs with enterprise systems via secure APIs • Lead development of enterprise agentic AI platforms and reusable frameworks • Establish MLOps, observability, CI/CD and agent lifecycle governance • Apply AI and analytics to cybersecurity data from SIEM, IAM and SOAR platforms

• Assist in structuring complex business and cybersecurity problems into data-driven hypotheses • Develop agentic AI systems and RAG pipelines • Implement MLOps best practices • Automate cybersecurity workflows using AI • Communicate technical concepts clearly to stakeholders