Forward Deployed Engineer, Frontier GenAI

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Company Overview

A leading professional services and technology organization helps enterprises accelerate digital transformation through advanced engineering, AI, data, cloud, and industry-specific solutions. The company partners with organizations across industries to design, build, and operate innovative technology platforms that drive business value and operational excellence.

The organization is seeking a Forward Deployed Engineer, Frontier GenAI to work directly with clients in designing, prototyping, and delivering enterprise-scale Generative AI solutions. This role combines software engineering, AI solution development, client engagement, and strategic problem-solving to help organizations realize measurable business impact through advanced AI technologies.

The successful candidate will work closely with technical and business stakeholders, rapidly translating high-value AI use cases into production-ready solutions. This position is ideal for professionals who thrive in fast-paced environments and enjoy operating at the intersection of engineering, product development, and client success.

Key Responsibilities

Client Engagement

• Partner directly with clients to identify business needs and translate high-value Generative AI opportunities into practical solutions.
• Collaborate with business leaders, product owners, architects, and engineers to align priorities and delivery objectives.
• Lead workshops and working sessions to shape solution strategies and drive successful client outcomes.
• Prototype and deploy AI-powered solutions using industry expertise and emerging technologies.
• Contribute independently within delivery teams while mentoring junior team members.

Solution Engineering

• Build AI-enabled applications, agentic platforms, and intelligent workflows across enterprise AI environments.
• Develop scalable AI engineering patterns, tool integration strategies, and human-in-the-loop controls.
• Make architecture decisions that balance quality, safety, latency, cost efficiency, and model risk.
• Deliver production-grade code following best practices for testing, CI/CD, logging, version control, and documentation.
• Design extensible functionality and contribute to sprint planning and solution architecture discussions.
• Create reusable assets such as code libraries, prompt frameworks, runbooks, and reference implementations.

Required Qualifications

• Bachelor’s degree (or equivalent) in Computer Science, Data Science, Engineering, or a related field.
• 3+ years of experience in software engineering, data engineering, data science, or analytics engineering.
• 1+ years of hands-on experience building and deploying Generative AI or LLM-powered solutions in production or client environments.
• 1+ years of experience with at least one major Frontier GenAI platform, including Anthropic, Google, or OpenAI technologies.
• Experience with platforms and products such as Claude API, Claude for Enterprise, Claude Code, Gemini API, Vertex AI Agent Builder, GPT-4o, Assistants API, Responses API, or OpenAI Agents SDK.
• 1+ years of experience leading project workstreams and translating business challenges into AI-powered solutions.
• Experience building reliable, maintainable, and well-documented software.
• Ability to travel approximately 50% based on client and project requirements.
• Eligibility to work within applicable employment authorization requirements.

Preferred Qualifications

• Experience working with cloud platforms such as AWS, Microsoft Azure, and/or Google Cloud Platform.
• Proven ability to collaborate directly with client technical teams and program stakeholders in dynamic delivery environments.
• Experience in data engineering technologies such as Spark, Airflow, dbt, streaming platforms, and data modeling.
• Background in machine learning, data science, feature engineering, experimentation, or model evaluation.
• Familiarity with MLOps and LLMOps practices, including evaluation frameworks, model monitoring, and prompt management.
• Experience integrating LLM solutions with enterprise systems through APIs, microservices, or event-driven architectures.
• Experience working within hybrid onshore/offshore delivery teams.
• Understanding of security, privacy, governance, and compliance considerations for enterprise AI solutions.

Disclaimer

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