AI Solutions Engineer - GenAI / Agentic AI

Role Overview

We are seeking a client-facing AI Solutions Engineer to lead the design, coordination, and delivery of enterprise-grade GenAI and agentic AI solutions.

This role sits at the intersection of business, AI technology, and delivery execution. The ideal candidate is someone who can confidently engage with client stakeholders, translate business needs into actionable technical plans, and drive execution across distributed engineering teams.

Rather than being purely hands-on, this role emphasizes solutioning, communication, and delivery ownership, with sufficient technical depth to guide architecture and ensure high-quality implementation.

Key ResponsibilitiesClient Engagement & Solutioning

• Act as the primary technical point of contact for client stakeholders (business IT).
• Lead discovery sessions to understand:
• Business workflows
• Data sources and system landscape
• AI use cases and priorities
• Translate ambiguous business requirements into:
• Structured solution approaches
• High-level architecture designs
• Clear implementation roadmaps
• Present solution options, trade-offs, and recommendations in a clear, business-friendly manner.
  

Delivery Leadership & Coordination

• Own end-to-end delivery coordination for AI initiatives.
• Break down solutions into actionable workstreams for:
• AI/ML engineers
• Data engineers
• Backend/platform teams
• Work closely with offshore/onshore teams to:
• Align priorities
• Track progress
• Resolve blockers
• Ensure timely, high-quality delivery aligned with client expectations.
  

AI Solution Design (GenAI / Agentic Systems)

• Contribute to the design of AI solutions including:
• RAG-based knowledge systems
• LLM-powered copilots and agents
• Workflow automation with AI augmentation
• Guide decisions around:
• Data ingestion and document pipelines
• Retrieval strategies and vector databases
• Tool/API integrations with enterprise systems
• Ensure solutions are scalable, secure, and production-ready.
  

Enterprise Integration & Workflow Enablement

• Coordinate integration of AI solutions with enterprise platforms such as:
• CRM systems (e.g., DealCloud, Backstop)
• Data platforms (e.g., Snowflake)
• Workflow tools (e.g., Appian)
• Work with engineering teams to define:
• API contracts
• Data flow patterns
• Secure access and governance controls
  

Quality, Governance & Continuous Improvement

• Ensure solutions meet standards for:
• Reliability
• Observability
• Security and compliance
• Identify opportunities to improve:
• Retrieval quality
• System performance
• User experience
• Promote reusable patterns and best practices across projects.
  

Required Qualifications

• 7–10 years of experience in software engineering, AI engineering, or solution architecture.
• 1 years of experience working with GenAI / LLM-based applications (RAG, copilots, or similar).
• Strong experience in client-facing roles with the ability to communicate effectively with both technical and non-technical stakeholders.
• Proven ability to translate business requirements into technical solutions.
• Experience coordinating or leading cross-functional engineering teams.
• Solid understanding of:
• APIs and system integrations (REST, OAuth)
• Data pipelines and enterprise systems
• Cloud platforms (AWS, Azure, or GCP)
  

Preferred Qualifications

• Experience with tools/frameworks such as:
• LangChain, LlamaIndex
• Pinecone or other vector databases
• Azure OpenAI or similar platforms
• Familiarity with enterprise systems like:
• Snowflake
• Appian
• CRM platforms (DealCloud, Backstop, etc.)
• Experience working in consulting or client delivery environments.
• Exposure to agentic AI workflows and orchestration concepts.
  

What Success Looks Like

• Client stakeholders view you as a trusted advisor who can bridge business and technology.
• Requirements are clearly translated into structured execution plans.
• Engineering teams are aligned, productive, and unblocked.
• AI solutions are delivered on time and meet real business needs.
• Systems are designed for scalability, reuse, and long-term value.
  
  

Why This Role Matters

This role is critical to ensuring that AI initiatives move beyond experimentation into real, production-grade enterprise solutions. You will play a key role in enabling organizations to leverage AI effectively by connecting strategy, technology, and execution.

The right candidate will combine strong communication skills, practical technical understanding, and delivery leadership to drive meaningful business outcomes through AI.

Skills: ai,api,llm