We’re looking for a hands-on backend expert who can take our FastAPI-based platform to the next level: production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. WHAT YOU'LL BUILD 1. Core Backend Enhancements Build APIs Harden security (OAuth2/JWT, rate-limiting, SecretManager) and observability (structured logging, tracing) Add CI/CD, test automation, ,health checks and SLO dashboards 2. Awesome UI Interfaces React.js/Next.js, Redact/Context, Tailwind / MUI / Custom-CSS / Shadcn / Axios 3. LLM & Agentic Services Design micro/mini-services that host and route to OpenAI, Anthropic, local HF models, embeddings & RAG pipelines Implement autonomous/recursive agents that orchestrate multi-step chains (Tools, Memory, Planning) 4. Model-Inference Infrastructure Spin up GPU / CPU inference servers behind an API gateway Optimize throughput with batching, streaming, quantization & caching (Redis / pgvector) 5. NLP & Data Services Own the NLP stack: Transformers for classification, extraction, and embedding generation. Build data pipelines that join aggregated business metrics with model telemetry for analytics TECH STACK YOU'LL WORK WITH 1.Fullstack/Backend Infrastructure • Python, FastAPI, Starlette, Pydantic • Async SQLAlchemy, Postgres, Alembic, pgvector • Docker, Kubernetes, or ECS/Fargate - AWS (Or) GCP • Redis / RabbitMQ / Celery (jobs & caching) • Prometheus, Grafana, OpenTelemetry • If you are a full-stack person, then - react.js / next.js / shadcn / tailwind.css / MUI 2.AI / NLP • HuggingFace Transformers, LangChain / Llama-Index, Torch / TensorRT • OpenAI, Anthropic, Azure OpenAI, Cohere APIs • Vector search (Pinecone, Qdrant, PGVector) 3. Tooling • Pytest, GitHub Actions • Terraform / CDK preferred MUST HAVE EXPERIENCE • 3+ yrs building production Python REST APIs (FastAPI, Flask, or Django-REST) • SQL schema design & query optimization in Postgres (CTEs, JSONB) • Deep knowledge of async patterns & concurrency (asyncio, AnyIO, celery) • Crafted awesome UI Applications that integrate with the backend API • Hands-on with RAG, LLM/embedding workflows, prompt-engineering & at least one of “agent-ops” frameworks (LangGraph, CrewAI, AutoGen) • Cloud container orchestration (Any of K8s, ECS, GKE, AKS, etc.) • CI/CD pipelines and infra-as-code NICE-TO-HAVE EXPERIENCE • Streaming protocols (Server-Sent Events, WebSockets, gRPC) • NGINX Ingress / AWS API Gateway • RBAC / multi-tenant SaaS security hardening • Data privacy, PII redaction, secure key vault integrations • Bitemporal or event-sourced data models WHY DOES THIS ROLE MATTER? We’re growing fast. Products are live, but evolving. Challenges are real, and the opportunity to own systems end-to-end is massive. You’ll lead how we scale AI services, work directly with the founder, and shape what the next wave of our platform looks like. If you’re looking for meaningful ownership and a chance to work on hard, forward-looking problems, this role is for you.

You are seeking a hands-on backend expert to elevate your FastAPI-based platform to the next level by developing production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. In this role, you will be responsible for various key areas: 1. Core Backend Enhancements: - Building APIs - Strengthening security with OAuth2/JWT, rate-limiting, SecretManager, and enhancing observability through structured logging and tracing - Adding CI/CD, test automation, health checks, and SLO dashboards 2. Awesome UI Interfaces: - Developing UI interfaces using React.js/Next.js, Redact/Context, and various CSS frameworks like Tailwind, MUI, Custom-CSS, and Shadcn 3. LLM & Agentic Services: - Designing micro/mini-services to host and route to platforms such as OpenAI, Anthropic, local HF models, embeddings & RAG pipelines - Implementing autonomous/recursive agents that orchestrate multi-step chains for Tools, Memory, and Planning 4. Model-Inference Infrastructure: - Setting up GPU/CPU inference servers behind an API gateway - Optimizing throughput with techniques like batching, streaming, quantization, and caching using tools like Redis and pgvector 5. NLP & Data Services: - Managing the NLP stack with Transformers for classification, extraction, and embedding generation - Building data pipelines to combine aggregated business metrics with model telemetry for analytics You will be working with a tech stack that includes Python, FastAPI, Starlette, Pydantic, Async SQLAlchemy, Postgres, Docker, Kubernetes, AWS/GCP, Redis, RabbitMQ, Celery, Prometheus, Grafana, OpenTelemetry, and more. Experience in building production Python REST APIs, SQL schema design in Postgres, async patterns & concurrency, UI application development, RAG, LLM/embedding workflows, cloud container orchestration, and CI/CD pipelines is essential for this role. Additionally, experience with streaming protocols, NGINX Ingress, SaaS security hardening, data privacy, event-sourced data models, and other related technologies would be advantageous. This role offers the opportunity to work on evolving products, tackle real challenges, and lead the scaling of AI services while working closely with the founder to shape the future of the platform. If you are looking for meaningful ownership and the chance to solve forward-looking problems, this role could be the right fit for you.,

As a hands-on backend expert, you will be responsible for taking our FastAPI-based platform to the next level by building production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. Please note that this role is being hired for one of our client companies, and the company name will be disclosed during the interview process. In this role, you will have the opportunity to work on the following key areas: Core Backend Enhancements: - Build APIs - Harden security with OAuth2/JWT, rate-limiting, SecretManager, and observability with structured logging and tracing - Implement CI/CD, test automation, health checks, and SLO dashboards Awesome UI Interfaces: - Develop UI interfaces using React.js/Next.js, Redact/Context, and various CSS frameworks like Tailwind, MUI, Custom-CSS, and Shadcn LLM & Agentic Services: - Design micro/mini-services to host and route to OpenAI, Anthropic, local HF models, embeddings, and RAG pipelines - Implement autonomous/recursive agents that orchestrate multi-step chains including Tools, Memory, and Planning Model-Inference Infrastructure: - Set up GPU/CPU inference servers behind an API gateway - Optimize throughput with batching, streaming, quantization, and caching using technologies like Redis and pgvector NLP & Data Services: - Own the NLP stack focusing on Transformers for classification, extraction, and embedding generation - Build data pipelines that combine aggregated business metrics with model telemetry for analytics You will be working with the following tech stack: - Python, FastAPI, Starlette, Pydantic - Async SQLAlchemy, Postgres, Alembic, pgvector - Docker, Kubernetes, or ECS/Fargate on AWS or GCP - Redis, RabbitMQ, Celery for jobs and caching - Prometheus, Grafana, OpenTelemetry - HuggingFace Transformers, LangChain, Torch, TensorRT - OpenAI, Anthropic, Azure OpenAI, Cohere APIs - Pytest, GitHub Actions - Terraform or CDK To be successful in this role, you must have: - 3+ years of experience building production Python REST APIs using FastAPI, Flask, or Django-REST - Strong SQL schema design and query optimization skills in Postgres - Deep knowledge of async patterns and concurrency - Hands-on experience with UI applications that integrate with backend APIs - Experience with RAG, LLM/embedding workflows, prompt-engineering, and agent-ops frameworks - Cloud container orchestration experience - Proficiency in CI/CD pipelines and infrastructure-as-code Nice-to-have experience includes familiarity with streaming protocols, NGINX Ingress, RBAC, multi-tenant SaaS security, data privacy, event-sourced data models, and more. This role is crucial as our products are live and evolving rapidly. You will have the opportunity to own systems end-to-end, scale AI services, work closely with the founder, and shape the future of our platform. If you are seeking meaningful ownership and enjoy working on challenging, forward-looking problems, this role is perfect for you.,