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We're looking for a talented Software Engineer with enthusiasm for AI/GenAI to join our innovation-focused team building agentic AI systems autonomous, reasoning-driven software agents capable of orchestrating complex tasks across tools, APIs, and data sources.
You'll design and build scalable backend systems that integrate large language models (LLMs) and other AI technologies into production-grade services. This role blends backend engineering, AI integration, and rapid prototyping, with room to learn, experiment, and deliver impactful, scalable solutions.
Architect and implement distributed services that power AI-driven applications.
Implement multi-step reasoning pipelines, retrieval-augmented generation (RAG), and domain-specific AI capabilities.
Build robust APIs, plugins, and integrations enabling AI agents to interact with external systems and data sources.
Create and refine proof-of-concepts, validating ideas quickly before scaling to production.
Implement monitoring, evaluation, and logging systems to track AI-powered features in production.
Work closely with product managers, designers, data scientists, and AI engineers to deliver user-focused solutions.
Stay curious about emerging AI frameworks, tools, and best practices to improve reasoning, planning, and autonomy in backend services.

We are seeking an experienced Generative AI Engineer to join our AI squad at our company. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.

Required Forward Deployed Engineer II, GenAI, Cloud
About the job
As a Generative Artificial Intelligence (GenAI) Forward Deployed Engineer, you will be an embedded builder bridging the gap between frontier artificial intelligence (AI) products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customers environment.
In this role, you will manage blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into our future product roadmap.It's an exciting time to join our Go-To-Market team, leading the AI revolution for businesses worldwide. Youll excel by leveraging our brand credibility-a legacy built on inventing foundational technologies and proven at scale. Well provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. Were a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era-the market is yours.
Responsibilities
Serve as the primary developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment.
Architect and code the connective tissue between our AI products and customer's live infrastructure (e.g., APIs, legacy data silos, and security perimeters).
Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
Identify repeatable field patterns and technical friction points in our AI stack, converting them into reusable modules or product feature requests for the engineering teams.
Deliver engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.

Were looking for a hands-on Senior AI Engineer to both build and guide. Youll architect and ship production GenAI systems while mentoring engineers - keeping one hand on the keyboard and one eye on the roadmap. This isnt a seat at a whiteboard - its a role for someone who can write a RAG pipeline in the morning and run a technical design review in the afternoon.Youll work on client-facing projects, building AI systems that go live across organizations and industries.
What Youll Do
Lead the design and delivery of end-to-end GenAI systems - from prototype to production
Write production-quality code, review PRs, and set a high engineering bar
Build and deploy LLM-powered applications (RAG pipelines, agents, fine-tuned models)
Define architecture patterns for prompt engineering, retrieval pipelines, and model evaluation
Partner with product, data, and platform teams to deliver real-world AI solutions
Mentor engineers, contribute to design reviews, and provide technical guidance
Evaluate and introduce new tools, models, and frameworks.

Required Forward Deployed Engineer III, GenAI, Cloud
About the job
As a GenAI Forward Deployed Engineer, you will be an embedded builder bridging the gap between frontier AI products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customers environment.
In this role, you will manage blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into our future product roadmap.
It's an exciting time to join our Go-To-Market team, leading the AI revolution for businesses worldwide. Youll excel by leveraging our brand credibility-a legacy built on inventing foundational technologies and proven at scale. Well provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. Were a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era-the market is yours.
Responsibilities
Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment.
Architect and code the connective tissue between ourAI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
Identify repeatable field patterns and technical friction points in our AI stack, converting them into reusable modules or product feature requests for the Engineering teams.
Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.