Lead AI Engineer in United States at Jobgether
Explore Related Opportunities
Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead AI Engineer based in United States.
This role sits at the forefront of building and scaling next-generation generative AI systems in production environments. You will lead the technical direction of AI engineering initiatives, guiding teams that design, develop, and deploy advanced GenAI and agentic solutions. Acting as both a hands-on architect and technical leader, you will shape how AI capabilities are translated into scalable, reliable, and cost-efficient systems that solve real business problems. You will collaborate closely with product managers, designers, and business stakeholders to ensure alignment between technical execution and product vision. The role requires balancing innovation with engineering rigor, ensuring responsible AI practices and production-grade reliability. You will also play a key role in mentoring engineers and elevating the overall AI engineering maturity of the organization.
- Lead and mentor a cross-functional team of software engineers, data scientists, and AI specialists delivering GenAI-powered solutions in production environments.
- Define technical architecture and engineering direction for scalable, reliable, and maintainable AI systems across multiple initiatives.
- Guide the design and optimization of end-to-end AI solutions, ensuring strong performance, cost efficiency, and production readiness.
- Collaborate with product managers, designers, and business stakeholders to translate business needs into robust AI-driven technical solutions.
- Establish and promote best practices in AI engineering, including testing, monitoring, responsible AI, guardrails, documentation, and CI/CD integration.
- Provide architectural oversight across AI systems, balancing rapid experimentation with disciplined delivery in iterative, safe release cycles.
- Review designs, code, and system implementations to ensure technical quality, consistency, and adherence to engineering standards.
- Drive optimization strategies for GenAI applications, including model tuning, RAG pipelines, and LLM performance improvements.
- 8+ years of experience in software engineering, AI engineering, or machine learning roles, including leadership responsibilities in technical teams.
- Strong expertise in Python and modern software engineering practices, including CI/CD, testing frameworks, version control, and distributed system design.
- Proven experience designing and deploying end-to-end AI systems in production, ensuring scalability, reliability, and maintainability.
- Deep knowledge of generative AI, LLMs, and agentic frameworks, with hands-on experience building RAG pipelines and integrating vector databases.
- Experience deploying AI/ML solutions on cloud platforms using containers, orchestration tools, and automated CI/CD pipelines.
- Strong understanding of LLMOps, observability, monitoring, and production AI system lifecycle management.
- Experience with model fine-tuning, adaptation, and ML/NLP frameworks for production-grade applications.
- Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders and influence senior decision-makers.
- Demonstrated leadership ability to mentor engineers, foster collaboration, and guide technical direction in fast-paced environments.
- Strong problem-solving skills with the ability to navigate ambiguity, align stakeholders, and drive consensus on technical decisions.
- Competitive annual salary ranging from $198,000 to $261,000 USD depending on experience and location
- Comprehensive health coverage including medical, dental, and vision insurance
- Flexible work arrangements with remote-friendly options
- Paid time off and additional leave policies supporting work-life balance
- Professional development opportunities and continuous learning support
- Retirement savings plans with employer contributions (where applicable)
- Inclusive, collaborative engineering culture focused on innovation and knowledge sharing
- Opportunity to work on cutting-edge generative AI systems with real-world impact