AI & Generative AI – Consultant / Architect / Engineer / Applied AI Scientist

AI & Generative AI – Consultant / Architect / Engineer / Applied AI Scientist

Location: United States
Employment Type: Full-Time
Work Arrangement: Onsite

About the Role

We are looking for experienced AI and Generative AI professionals to join our team across multiple areas, including AI Consulting, AI Architecture, AI Engineering, and Applied AI Research.

The ideal candidates will have hands-on experience building, deploying, architecting, or advising on Generative AI, Agentic AI, LLMs, AI platforms, and enterprise AI solutions.

Depending on your background and expertise, you may contribute to AI strategy and use-case discovery, design enterprise AI architecture, build production AI agents, or improve model performance through advanced machine learning techniques.

Areas of Opportunity1. AI Consultant

• Identify and evaluate high-value AI and automation opportunities.
• Conduct use-case discovery sessions and workshops with business stakeholders.
• Assess opportunities based on business value, technical feasibility, risk, data readiness, and adoption.
• Develop business cases, including expected benefits, costs, assumptions, and ROI.
• Translate business problems into clear requirements and specifications for engineering teams.
• Redesign business workflows to effectively incorporate AI.
• Define success metrics and measure business outcomes before and after implementation.
• Support stakeholder communication, change management, and AI adoption.

1. AI Architect

• Design scalable architectures for Generative AI and Agentic AI solutions.
• Define architecture for orchestration, tools, memory, retrieval, state management, model routing, and multi-agent workflows.
• Establish AI platform controls covering security, governance, auditability, data lineage, evaluation, human oversight, guardrails, cost management, and access control.
• Define standards for prompt management, versioning, evaluation, regression testing, rollback, and model drift.
• Evaluate build-versus-buy decisions and assess AI technology vendors.
• Design solutions aligned with enterprise security, compliance, and responsible AI requirements.
• Work with engineering and business teams to ensure AI architectures are scalable, secure, and production-ready.

1. AI Engineer

• Build and deploy production-ready AI and Agentic AI applications.
• Develop AI agents using retrieval, tool/function calling, orchestration, state management, and memory.
• Build enterprise retrieval solutions using embeddings, chunking, hybrid search, reranking, grounding, and citations.
• Deploy AI applications using cloud AI platforms such as Microsoft Azure AI Foundry.
• Implement evaluation frameworks, regression testing, tracing, monitoring, and cost/token telemetry.
• Integrate AI solutions with enterprise applications, databases, APIs, and business systems.
• Follow modern software engineering practices including CI/CD, containers, and infrastructure as code.

1. Applied AI Scientist

• Improve the performance and capabilities of Generative AI and Large Language Models.
• Develop and execute fine-tuning strategies including SFT, LoRA, QLoRA, and continued pre-training.
• Work with preference optimization techniques such as DPO, GRPO, reward modeling, RLHF, and RLAIF.
• Develop advanced prompting and context-engineering strategies.
• Design evaluation frameworks using golden datasets, LLM-as-a-judge, calibration, and drift detection.
• Develop and use synthetic data where appropriate for model training and evaluation.
• Optimize model selection and routing based on quality, performance, and cost.
• Conduct experiments and demonstrate measurable improvements in model performance.

Required Qualifications

Depending on the position and area of expertise, candidates should have:

• 5+ years of relevant professional experience in consulting, software engineering, AI/ML, data science, architecture, or a related field.
• Hands-on experience with Generative AI, LLMs, Agentic AI, or enterprise AI solutions.
• Experience delivering AI solutions or research into production or measurable business outcomes.
• Strong understanding of AI/ML concepts and modern Generative AI technologies.
• Experience working with cross-functional business and technical teams.
• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder management skills.

Technical Skills

Experience with one or more of the following is highly …