What you'll do
- Work closely with client teams to translate business challenges into production-ready AI solutions
- Lead architecture, development, and deployment of end-to-end AI and Generative AI solutions
- Design and implement Retrieval-Augmented Generation, agentic AI, and intelligent automation solutions
- Evaluate, adapt, and optimize LLM-based solutions for quality and performance
- Integrate AI capabilities into enterprise platforms in cloud and on-premises environments
- Build evaluation frameworks and monitor AI solutions for quality, latency, cost, and business impact
- Collaborate with business and technology teams to create scalable AI architectures and applications
- Contribute to Responsible AI, governance, and compliance initiatives
- Mentor junior engineers and promote engineering best practices
- Support client workshops, solution design sessions, and AI transformation initiatives
Key requirements
- 5+ years' experience
- Proficiency in Python and building production-grade AI applications
- Experience with LLM, Generative AI, Retrieval-Augmented Generation, and agentic AI
- Skilled in API design, data pipelines, and cloud platforms such as Azure, AWS, or GCP
- Knowledge of MLOps, CI/CD, containerization, and production deployment
- Understanding of Responsible AI and AI governance
- Experience with Enterprise Integrations and AI engineering best practices
- Computer Science / Engineering / Science, Technology, Engineering, and Mathematicspreferred
About the job
As an Forward Deployed Engineer, you'll work alongside client teams to bridge the gap between cutting - edge AI capabilities and real business outcomes. You will design, build, and deploy production - ready AI and Generative AI solutions, helping organizations accelerate innovation, improve operations, and unlock measurable business value.
You will:
Work closely with clients teams to rapidly translate business challenges into production - ready AI solutions;
Lead the architecture, development, and deployment of end-to-end AI and GenAI solutions, from data ingestion and enterprise integrations to production deployment and monitoring;
Design and implement Retrieval - Augmented Generation (RAG), agentic AI, and intelligent automation solutions that solve complex business challenges;
Evaluate, Adapt, and optimize LLM - based solutions to ensure quality, scalability, performance and cost efficiency;
Integrate AI capabilities into enterprise platforms across cloud and on - premises environments, following secure and scalable engineering practices;
Build evaluation frameworks and monitor AI solutions for quality, latency, cost, reliability, and business impact;
Collaborate with business and technology teams to translate business requirements into scalable AI architectures and applications;
Contribute to Responsible AI, governance, and compliance initiatives, including GDPR and the EU AI Act;
Mentor junior engineers, promote engineering best practices, and contribute to reusable AI assets and accelerators;
Support clients workshops, solutions design sessions, and AI transformation initiatives from ideation through production.
#WinningRequirements
To qualify for the role you must have:
Bachelor’s and/or Master's degree in Computer Science, Engineering, or a related STEM field;
5+ years of experience in software engineering, AI/ML, or data engineering, with hands - on experience delivering AI or Generative AI solutions;
Strong proficiency in Python and experience building production - grade AI applications;
Experience with LLM's, Retrieval - Augmented Generation (RAG), agentic AI, and modern AI engineering practices;
Experience designing scalable APIs, data pipelines, and cloud - native applications on Azure, AWS or GCP;
Familiarity with modern AI orchestration frameworks, enterprise integrations, and AI application development best practices;
Understanding of MLOps, CI/CD, containerization, and production deployment principles;
Knowledge of Responsible AI, model evaluation, and AI governance principles;
Experience leading technical teams and delivering high - quality client solutions;
Excellent communication, problem - solving, and stakeholder management skills, with the ability to bridge business and technology.




