Senior Consultant - AI Developer

The Senior AI Application Engineer will design and build reusable AI-powered applications and accelerators that support internal operations, consulting delivery, and client-facing innovation. This role will be responsible for translating business and product requirements into scalable technical solutions using commercial language models, orchestration frameworks, retrieval systems, and enterprise integrations.

• Design end-to-end AI application architecture for internal and client-facing use cases
• Define patterns for prompt orchestration, agent workflows, retrieval-augmented generation (RAG), tool calling, and enterprise integrations
• Select appropriate models, frameworks, vector stores, and deployment patterns based on cost, performance, and security considerations
• Establish reusable design patterns for future AI accelerators and company-owned IP

• Build production-grade AI applications, copilots, assistants, and workflow automations
• Lead development of reusable AI components that can be scaled across multiple engagements
• Translate roadmap initiatives into technical implementation plans, milestones, and deliverables
• Partner with product and business stakeholders to refine use cases into buildable solutions

• Evaluate and implement commercial LLMs through APIs and enterprise tooling
• Develop robust prompt strategies, context handling logic, tool usage patterns, and fallback mechanisms
• Design and optimize RAG pipelines using structured and unstructured enterprise knowledge sources
• Improve output quality, reliability, and usability of AI applications through testing and iteration

• Define coding standards, deployment standards, logging, monitoring, guardrails, and evaluation practices for AI applications
• Implement mechanisms for observability, tracing, prompt versioning, and response quality review
• Ensure solutions are secure, maintainable, scalable, and aligned with enterprise architecture principles
• Guide non-functional requirements including latency, reliability, token usage, and cost optimization

• Serve as the technical lead for AI engineering efforts
• Mentor and guide the AI Developer / GenAI Engineer
• Support technical decision-making, effort estimation, and feasibility assessments
• Collaborate with cross-functional teams including product, architecture, delivery, QA, and operations

• Participate in discovery sessions with business and delivery teams to identify opportunities for AI enablement
• Work with consulting, sales, and solution engineering teams to understand repeatable use cases
• Support demos, pilots, proofs of concept, and internal enablement where required

• Define testing and evaluation methods for AI outputs, workflows, and workflows involving enterprise data
• Improve system quality through prompt tuning, retrieval tuning, workflow redesign, model selection, and structured feedback loops
• Contribute to AI roadmap recommendations from a technical feasibility and maturity perspective

• Strong software engineering background
• Experience building AI/LLM-powered applications
• Experience with APIs for OpenAI / Azure OpenAI / Anthropic / Google or similar
• Experience with Python and/or Node.js
• Experience with RAG, vector databases, embeddings, chunking, retrieval strategies
• Experience with orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or equivalent)
• Strong knowledge of cloud architecture and secure integrations
• Experience with prompt engineering, evaluation, and AI application debugging
• Ability to design scalable reusable systems

• Experience with enterprise SaaS ecosystems such as Salesforce / Oracle / Microsoft
• Experience with agentic workflows
• Experience with observability/evaluation platforms
• Experience working in consulting or product-based delivery organizations
• Exposure to AI governance, data privacy, and model risk considerations

• Establishes the baseline architecture for AI applications
• Builds first reusable accelerator(s)
• Defines engineering standards for GenAI delivery
• Enables fast prototyping with production-minded design
• Acts as technical backbone for roadmap execution