Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Lead a small team to design, build, and deploy production-grade generative AI systems using Python, RAG pipelines, vector databases, and cloud platforms while mentoring engineers and aligning solutions with business goals.
Build an AI-powered reliability assistant using LLMs, vector search, and RAG to help engineers resolve incidents faster by retrieving and synthesizing data from observability tools and past incidents.
Lead the design and deployment of AI/ML features for a commercial real estate SaaS platform, including LLM-powered tools and custom domain models, while setting engineering standards and mentoring teams.
Build AI-powered full-stack apps for Capital Markets clients using Python, FastAPI, React, and GenAI tools like RAG and LLMs.
Design and implement AI-enabled, cloud-native architectures for enterprise clients, focusing on RAG, agentic AI, and cloud modernization using Azure/GCP.
Design and build secure, compliant AI/ML platforms on AWS and Azure for a large bank, including MLOps pipelines, guardrails, and observability for regulated environments.
Lead a team to design, build, and deploy AI/ML systems including generative models and vector databases, using Python, PySpark, SQL, and cloud platforms.
Lead AI/ML and GenAI solution development, architect full-stack systems on GCP/Azure, and mentor teams while bridging business needs with technical execution.
Build and deploy production-grade ML systems for utility operations, focusing on time-series forecasting, anomaly detection, and geospatial intelligence with MLOps and cloud/on-prem deployments.
Build and maintain scalable Azure and Microsoft Fabric data pipelines and lakehouse/warehouse solutions to power generative AI, RAG, and intelligent agents for enterprise analytics.
Build and operate the ML infrastructure powering an AI assistant, focusing on model training, deployment, inference, and observability to enable reliable, scalable, and cost-efficient production systems.
Build and deploy AI-powered Python full-stack applications, integrating LLMs, APIs, and MCP workflows to connect AI systems with customer platforms and data sources.
Build and scale the backend infrastructure for an AI-powered analytics platform that processes customer feedback, integrating data pipelines and optimizing storage for LLM-driven insights.
Builds and deploys AI-driven backend systems and cloud infrastructure using Python/TypeScript, focusing on scalable APIs, MLOps, and modern AI patterns like RAG.
Build and ship LLM-powered AI agent workflows that orchestrate multi-step tasks, integrate tools, and turn probabilistic model outputs into reliable user experiences.
Design and maintain AI-focused data catalogues, metadata schemas, and lineage systems to ensure high-quality, auditable AI outputs for clients in regulated industries.
Build and optimize multi-agent AI systems using LangChain/LangGraph, FastAPI, and RAG pipelines for production-grade performance and security.
Designs, builds, and deploys production-grade AI agents, copilots, and intelligent automations to transform business processes using enterprise AI platforms and low-code/no-code tools.
Build and operate HERE’s enterprise AI Hub: shared runtime, CI/CD, model registry, and observability for scalable, secure AI deployments and intelligent agents.
Builds cloud-native, full-stack products (React/Node.js/PostgreSQL) for a venture-funded startup focused on real estate automation, integrating generative AI (LLMs, vector DBs) and DevOps pipelines to streamline strata management workflows.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
