Senior Full Stack Developer / Solutions Architect

Position Overview:

We are seeking a Senior Full Stack Developer who can also operate as a Solutions Architect to lead the design, development, and delivery of AI-focused solutions for our clients. This role sits at the intersection of hands-on engineering, client advisory, and architecture. You will partner directly with leadership to help organizations adopt AI in practical, secure, and scalable ways. We are not building the next foundational AI platform. Our work is about helping companies use AI effectively. That includes building lightweight wrappers around existing models, integrating AI tools into client workflows, creating internal AI gateways and orchestration layers, securing and anonymizing client data, and advising on build versus buy decisions as the AI tooling landscape continues to evolve. You will collaborate with our AI team to answer the harder strategic questions. How does AI change the relevance of their existing software? What is the right rollout approach? Where should they invest engineering effort, and where should they adopt off the shelf tools?

Our Ideal Candidate:

You are a senior builder and a strategic thinker. You enjoy translating client problems into architecture, and you can move between writing code, leading a small dev team, and advising a client on strategy. You are pragmatic about AI. You understand the difference between hype and capability, and can confidently recommend the right path forward, whether that means building, buying, integrating, or waiting. You take pride in shipping clean, secure, and maintainable solutions that solve real business problems.

Required Qualifications and Skills Experience:

Minimum 5 to 8 years of professional full stack development experience, with at least 2 years working hands on with AI APIs, LLM integrations, or AI-enhanced applications.

Education:

Bachelor's degree in Computer Science, Software Engineering, or a related field (preferred but not required). Stack-agnostic technical fluency. We care more about the right person than a specific stack, but candidates should be strong in modern web frameworks (React, Node.js, Python, FastAPI, etc.), backend systems, databases, and at least one major cloud platform (AWS, Azure, or GCP). Hands-on experience with the modern AI tooling layer, including orchestration frameworks (LangChain or similar), vector databases (Pinecone or similar), retrieval-augmented generation (RAG) patterns, and agentic workflows. Direct experience integrating LLM APIs from providers such as OpenAI, Anthropic, Google, and open-source models via Hugging Face or comparable platforms. Strong understanding of model routing, AI gateways, prompt management, and cost or usage controls for enterprise AI rollouts. Working knowledge of data anonymization, PII handling, prompt injection defense, and AI security best practices. Comfortable presenting architecture decisions and build versus buy recommendations directly to clients, founders, and senior stakeholders. Strong written and verbal communication skills, with the ability to lead a small cross-functional dev team when projects require it.

Bonus:

Experience with building internal automations, AI governance tooling, or SaaS productization.

Bonus:

Experience with brand voice modeling, content automation, or marketing technology builds.

Key Roles and Responsibilities AI Solutions Architecture:

Design end to end AI solutions for client engagements, including system architecture, data flow, model selection, and integration patterns across multiple AI providers.

Hands-On Development:

Build production applications, wrappers, and integrations using modern frameworks and AI APIs. Own implementation from prototype through deployment, including QA, monitoring, and iteration.

Client Advisory:

Partner directly with clients to translate business goals into technical roadmaps, advise on build versus buy decisions, and shape AI rollout strategies whether top down, bottom up, or hybrid.

AI Governance and Control Platforms:

Build platforms that monitor and control AI usage inside client organizations, including model gateways, permissions, audit trails, and employee-facing AI chat environments.

Orchestration and Data Portals:

Develop orchestration layers, data portals, and internal AI workflow tools that allow clients to centralize, govern, and manage their AI operations across teams.

Data Security and Anonymization:

Implement data anonymization, PII redaction, access control, and security guardrails for client AI workflows. Stay current on prompt injection, data leakage, and emerging AI risk patterns. Build vs

Buy Evaluations:

Continuously evaluate emerging AI tools and platforms. Help clients decide when to build, when to buy, and when to wait. Address how AI advances may impact the relevance of their existing software stack.

Team Leadership:

Lead small cross-functional dev teams on larger builds when needed. Set technical direction, review code, and mentor team members on engineering and AI best practices.

Documentation and Knowledge Transfer:

Maintain clean technical documentation. Train internal teams and client stakeholders on the systems we build so they remain self sufficient post launch.

Pay:

$130,000.00

• $150,000.

00 per year

Benefits:

401(k) Dental insurance Retirement plan

Work Location:

In person Senior Full Stack Developer / Solutions Architect Clarendon Hills, IL 60514 $130,000

• $150,000 a year
• Full-time $130,000
• $150,000 a year

•

Full-time Position Overview:

We are seeking a Senior Full Stack Developer who can also operate as a Solutions Architect to lead the design, development, and delivery of AI-focused solutions for our clients. This role sits at the intersection of hands-on engineering, client advisory, and architecture. You will partner directly with leadership to help organizations adopt AI in practical, secure, and scalable ways. We are not building the next foundational AI platform. Our work is about helping companies use AI effectively. That includes building lightweight wrappers around existing models, integrating AI tools into client workflows, creating internal AI gateways and orchestration layers, securing and anonymizing client data, and advising on build versus buy decisions as the AI tooling landscape continues to evolve. You will collaborate with our AI team to answer the harder strategic questions. How does AI change the relevance of their existing software? What is the right rollout approach? Where should they invest engineering effort, and where should they adopt off the shelf tools?

Our Ideal Candidate:

You are a senior builder and a strategic thinker. You enjoy translating client problems into architecture, and you can move between writing code, leading a small dev team, and advising a client on strategy. You are pragmatic about AI. You understand the difference between hype and capability, and can confidently recommend the right path forward, whether that means building, buying, integrating, or waiting. You take pride in shipping clean, secure, and maintainable solutions that solve real business problems.

Required Qualifications and Skills Experience:

Minimum 5 to 8 years of professional full stack development experience, with at least 2 years working hands on with AI APIs, LLM integrations, or AI-enhanced applications.

Education:

Bachelor's degree in Computer Science, Software Engineering, or a related field (preferred but not required). Stack-agnostic technical fluency. We care more about the right person than a specific stack, but candidates should be strong in modern web frameworks (React, Node.js, Python, FastAPI, etc.), backend systems, databases, and at least one major cloud platform (AWS, Azure, or GCP). Hands-on experience with the modern AI tooling layer, including orchestration frameworks (LangChain or similar), vector databases (Pinecone or similar), retrieval-augmented generation (RAG) patterns, and agentic workflows. Direct experience integrating LLM APIs from providers such as OpenAI, Anthropic, Google, and open-source models via Hugging Face or comparable platforms. Strong understanding of model routing, AI gateways, prompt management, and cost or usage controls for enterprise AI rollouts. Working knowledge of data anonymization, PII handling, prompt injection defense, and AI security best practices. Comfortable presenting architecture decisions and build versus buy recommendations directly to clients, founders, and senior stakeholders. Strong written and verbal communication skills, with the ability to lead a small cross-functional dev team when projects require it.

Bonus:

Experience with building internal automations, AI governance tooling, or SaaS productization.

Bonus:

Experience with brand voice modeling, content automation, or marketing technology builds.

Key Roles and Responsibilities AI Solutions Architecture:

Design end to end AI solutions for client engagements, including system architecture, data flow, model selection, and integration patterns across multiple AI providers.

Hands-On Development:

Build production applications, wrappers, and integrations using modern frameworks and AI APIs. Own implementation from prototype through deployment, including QA, monitoring, and iteration.

Client Advisory:

Partner directly with clients to translate business goals into technical roadmaps, advise on build versus buy decisions, and shape AI rollout strategies whether top down, bottom up, or hybrid.

AI Governance and Control Platforms:

Build platforms that monitor and control AI usage inside client organizations, including model gateways, permissions, audit trails, and employee-facing AI chat environments.

Orchestration and Data Portals:

Develop orchestration layers, data portals, and internal AI workflow tools that allow clients to centralize, govern, and manage their AI operations across teams.

Data Security and Anonymization:

Implement data anonymization, PII redaction, access control, and security guardrails for client AI workflows. Stay current on prompt injection, data leakage, and emerging AI risk patterns. Build vs

Buy Evaluations:

Continuously evaluate emerging AI tools and platforms. Help clients decide when to build, when to buy, and when to wait. Address how AI advances may impact the relevance of their existing software stack.

Team Leadership:

Lead small cross-functional dev teams on larger builds when needed. Set technical direction, review code, and mentor team members on engineering and AI best practices.

Documentation and Knowledge Transfer:

Maintain clean technical documentation. Train internal teams and client stakeholders on the systems we build so they remain self sufficient post launch.

Pay:

$130,000.00

• $150,000.

00 per year

Benefits:

401(k) Dental insurance Retirement plan

Work Location:

In person