BICP, a San Diego-based consulting firm specializing in AI, Data & Analytics, is seeking an experienced Forward Deployed AI Engineer to join our team in an embedded capacity with one of our strategic clients in the apparel and retail industry.

This is a hands-on engineering role focused on turning high-value business problems into production-ready AI solutions. You will work directly with business, Product, Data Science, Data Engineering, and technology teams to identify opportunities, rapidly prototype solutions, and build the applications and integrations required to operationalize AI within real business workflows.

The ideal candidate combines strong software engineering fundamentals with hands-on experience building Generative AI, LLM, and Agentic AI applications. Just as importantly, you are comfortable working directly with business stakeholders, navigating ambiguity, and taking ownership of a problem from initial concept through production and adoption.

This is not a research-only or traditional requirements-driven engineering role. We are looking for someone who can understand the business problem, determine how AI can best address it, and then build the solution.

What You'll Do

Work directly with business and Product teams to identify and define high-value opportunities for AI, GenAI, and Agentic AI.
Translate ambiguous business problems into technical requirements, solution designs, prototypes, and production-ready applications.
Design and build LLM-powered applications, AI agents, copilots, intelligent workflows, and other applied AI solutions.
Develop Agentic AI solutions capable of reasoning across business context, accessing enterprise data, calling tools and APIs, and taking actions within appropriate guardrails.
Build and implement RAG architectures, including embeddings, vector search, retrieval strategies, context management, and grounding against enterprise knowledge.
Integrate AI applications with enterprise data, APIs, SaaS applications, operational systems, and existing business workflows.
Develop backend services, APIs, orchestration layers, and application components required to operationalize AI use cases.
Prototype new AI capabilities quickly, validate them with end users, and iterate based on real-world feedback and measurable business value.
Partner with AI Platform, Architecture, Security, and Data teams to move solutions from experimentation into scalable and governed production environments.
Implement approaches for AI evaluation, testing, observability, guardrails, human-in-the-loop controls, and performance monitoring.
Evaluate foundation models, AI frameworks, agent architectures, and emerging technologies based on the requirements of specific business problems.
Optimize AI applications for accuracy, latency, reliability, scalability, and cost.
Troubleshoot complex technical and integration issues across AI models, applications, enterprise data, and business systems.
Develop reusable components and patterns that accelerate future AI use cases.
Communicate technical tradeoffs, opportunities, and limitations clearly to both technical and non-technical stakeholders.
Remain accountable for solutions beyond the prototype, helping drive them through production, adoption, measurement, and continuous improvement.

What We're Looking For

6+ years of experience across Software Engineering, Machine Learning Engineering, AI Engineering, Data Engineering, or related technical disciplines.
Significant hands-on experience building and deploying AI/ML or Generative AI applications in production environments.
Advanced proficiency with Python and strong software engineering fundamentals.
Hands-on experience with LLMs and modern GenAI development, including prompt engineering, structured outputs, function/tool calling, embeddings, and model APIs.
Experience building RAG applications using vector databases, enterprise search, or other retrieval technologies.
Experience developing or implementing AI agents and agentic workflows, including orchestration, tool use, context management, memory, and human-in-the-loop patterns.
Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, LlamaIndex, or comparable AI application frameworks.
Experience working with commercial and/or open-source foundation models through platforms such as OpenAI, Azure OpenAI, Anthropic, Amazon Bedrock, or equivalent technologies.
Strong understanding of APIs, microservices, application integration, cloud infrastructure, and modern software development practices.
Experience with at least one major cloud ecosystem such as Azure, AWS, or GCP.
Experience integrating AI applications with enterprise data sources, applications, APIs, and operational workflows.
Understanding of production AI concerns including evaluation, observability, security, privacy, reliability, latency, and cost.
Demonstrated ability to work directly with Product and business stakeholders rather than relying exclusively on predefined technical requirements.
Strong problem-solving skills and the ability to operate effectively when the solution is not immediately obvious.
Strong communication skills with the ability to explain complex technical concepts and tradeoffs to technical and non-technical audiences.

Preferred Experience

Experience operating in a Forward Deployed, Applied AI, Solutions Engineering, or similarly embedded technical role.
Direct experience taking Agentic AI applications from prototype into enterprise production.
Experience designing multi-step agent workflows involving enterprise data, APIs, tools, business rules, and human approvals.
Experience with AI evaluation frameworks, guardrails, observability, and LLMOps.
Experience with Snowflake, Databricks, or other modern enterprise data platforms.
Experience building AI solutions within retail, apparel, DTC, consumer products, e-commerce, or another consumer-oriented environment.
Familiarity with business domains such as merchandising, planning, supply chain, consumer intelligence, marketing, digital commerce, or retail operations.
Experience working in environments where AI solutions must meet enterprise security, governance, and data privacy requirements.

The Kind of Person Who Will Thrive in This Role

You are an engineer who wants to be close to the problem you're solving.
You don't need a perfectly written set of requirements before getting started. You are comfortable sitting with a business or Product team, understanding how people actually work, identifying where AI can create value, and turning that opportunity into a working solution.
You are technically deep enough to build, integrate, troubleshoot, and productionize sophisticated AI applications, but pragmatic enough to know that the objective isn't to use the most advanced technology—it's to solve the business problem.
You prototype quickly, learn from users, iterate, and take ownership beyond the demo. You care about whether the solution is adopted, trusted, and ultimately creates measurable value.
You understand that enterprise AI requires both velocity and discipline, and you know how to move quickly while working within appropriate architecture, security, data, and governance guardrails.
Most importantly, you operate with an ownership mindset:
Understand the problem. Build the solution. Get it into production. Make sure it works.

About BICP

BICP is a San Diego-based AI, Data & Analytics consultancy that helps organizations close the gap between strategic priorities and the specialized capabilities required to execute them. Our Forward Deployed practitioners work alongside client teams, bringing deep expertise across AI/ML, Data, Analytics, Product, and Architecture to move initiatives from idea to implementation, production, and measurable business impact.

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