Mid - AI Software Engineer- USA

At Cogniify, we believe AI should move beyond pilots and prototypes into real, governed, enterprise-scale production. Sharper Data. Smarter AI. Real Results.

We partner with Fortune 100 and global enterprises to advance AI from readiness through to production with the governance, financial discipline, and operational rigor that large organizations require. Our work is anchored in the 4S Intelligence framework Sharper Analytics, Smarter AI, Scalable Systems, and Secured Governance and spans strategy, engineering, and AI delivered as end-to-end ecosystems, not siloed projects. We don't sell a one-size-fits-all platform — every engagement is a custom-built solution designed around a client's specific problem, data, and constraints. Our philosophy is simple: clarity, trust, and measurable outcomes.

We're seeking a versatile AI-Enabled Full-Stack Engineer to bridge the gap between traditional web development and modern applied AI. You will own features end to end - from the user interface and backend APIs through LLM integration, retrieval-augmented generation (RAG), and agent workflows - and ship them into production user flows.

Unlike a research or model-training role, this position is about applied AI product delivery: taking modern LLM capabilities and turning them into fast, reliable, well-designed product features that real users depend on. You'll work across the stack, move quickly, and treat reliability, latency, and cost as first-class engineering concerns - not afterthoughts.

This role is built for an engineer who is equally comfortable crafting a responsive React interface, designing a clean backend API, and reasoning about context windows, tool invocation, and hallucination mitigation - someone who ships complete features, not just slices of them.

• Own features end to end - design and build scalable web features using modern frontend and backend stacks (TypeScript, React, Next.js, Python, FastAPI, Java, Spring Boot), from UI through API to data layer.

• Integrate applied AI into production - embed Large Language Model (LLM) APIs, vector search, embeddings, and RAG architectures directly into production user flows.

• Build agent and tool workflows - develop custom AI agents, manage context windows effectively, and implement structured tool invocation and Model Context Protocol (MCP) interfaces.

• Engineer for AI reliability - design for AI failure modes, latency constraints, token cost tracking, hallucination mitigation, and observability, so AI-powered features hold up under real production load.

• Shape AI-first user experiences - collaborate with product and design teams to craft intuitive, responsive, AI-driven experiences that feel fast and trustworthy.

• Deploy and operate at scale - containerize and scale services using Docker and Kubernetes (K8s) on cloud platforms (AWS, Azure, or GCP), with automated CI/CD pipelines.

• Raise the bar - contribute to shared patterns, evaluation practices, and reusable components that speed up future AI feature development across the team.

• 4-6+ years of professional full-stack software development experience, with recent hands-on work shipping production features.

• Frontend & backend depth - strong proficiency in JavaScript/TypeScript, modern UI frameworks (React, Next.js), and backend services (Node.js, Python, Java, Spring Boot).

• Applied AI/ML tooling - hands-on experience integrating LLM APIs, prompt engineering, vector databases, and RAG frameworks into real applications (not just experiments).

• System architecture fundamentals - solid understanding of RESTful APIs, relational and NoSQL databases, and cloud-native microservices.

• Cloud & infrastructure - hands-on experience with AWS (or Azure/GCP) and container orchestration using Kubernetes, including deploying and scaling production workloads.

• Production mindset - familiarity with AI observability, security guardrails, cost optimization, and evaluation metrics; you think about what happens after the demo works.

• Strong problem-solving ability - comfortable with ambiguity, able to break down an open-ended product requirement and independently deliver a well-reasoned, working solution.

• Collaboration and ownership - able to work closely with product, design, and senior engineers, take feedback well, and see features through from spec to stable production.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).

US East/West Coast: $130,000 - $150,000

Disclaimer: The base salary range is a guideline and may vary based on factors such as candidate experience, specialized skills, and geographical location. Actual compensation may include additional benefits and bonuses.

• Unlimited PTO.

• Please ask us about our very generous parental leave, much above industry standards!

• Entrepreneurial culture where pushing limits and taking risks is everyday business.

• Open communication with management and company leadership.

• Small, dynamic teams = massive impact.

• Medical, Dental and Vision coverage for employees.

• Access to Disability & Life insurance.

• Mental health and wellbeing support.

• Annual bonus program.

• Employer Stock Purchase Program (ESPP).

• Yearly team building experiences.

• Mentorship and sponsorship opportunities.

• Manager resources and support.

Cogniify is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic