Remote Senior Full-Stack AI Engineer: AI Features & Pipelines

TechTide Solutions; Northern, New York (KY, NY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

15 days PTO + US public holidays + +s

Paid parental leave

Remote work stipend

Annual learning budget

Job summary

TechTide Solutions is seeking an experienced software engineer to design and deliver AI-powered features end-to-end. You will work across the stack—from APIs and orchestration to slick frontend integrations—and build robust retrieval pipelines and evaluation harnesses for production.

You will evaluate data constraints to select models and guardrails, and establish reusable patterns for SDKs, caching, and cost/latency budgets. Collaboration with teams and clients is key.

Qualifications

• 5+ years of full-stack engineering with shipped LLM/ML-backed features.
• Proficiency in TypeScript or Python and comfortable across React and a modern backend.
• Hands-on experience with embeddings, retrieval augmented generation (RAG), and evaluation.
• Ability to judge when AI is the right tool for a given problem.

Responsibilities

• Design and ship AI features across the stack: APIs, orchestration, and front-end integration.
• Build retrieval pipelines, prompt flows, and evaluation harnesses for production.
• Collaborate with clients on data and constraints to select models and guardrails.
• Set reusable patterns: SDK choices, caching, and manage cost and latency budgets.

Skills

Full-stack engineering

TypeScript or Python

React and modern backend

Embeddings

RAG

Evaluation

Judgment on AI tools

Tools

React

TypeScript

Python

APIs

Retrieval pipelines

Job description

TechTide Solutions is seeking an experienced software engineer to design and deliver AI-powered features end-to-end. You will work across the stack—from APIs and orchestration to slick frontend integrations—and build robust retrieval pipelines and evaluation harnesses for production.

You will evaluate data constraints to select models and guardrails, and establish reusable patterns for SDKs, caching, and cost/latency budgets. Collaboration with teams and clients is key.