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Xerago - Senior AI Full Stack Developer - Python/React.js
Xerago - Senior AI Full Stack Developer - Python/React.jsXerago • Chennai
Xerago - Senior AI Full Stack Developer - Python / React.js

Xerago - Senior AI Full Stack Developer - Python / React.js

Xerago • Chennai
18 days ago
Job description

Roles & Responsibilities :

  • Architect scalable AI solutions : Define end-to-end reference architectures (LLM / RAG, NLP, vision, agentic workflows) that move cleanly from DemoBytes ? POC ? MVP ? Demoable ? Production.
  • Own full-stack delivery : Build features across data / ML, backend APIs / services (FastAPI / Flask), and lightweight UIs (React / Next.js) for demoable, user-ready outputs.
  • Rapid prototyping : Stand up POCs in days; harden validated solutions into MVP and production with incremental quality / security gates.
  • MLOps & platformization : Implement CI / CD / CT for models, datasets, prompts; automate evals, canary / rollback, versioning, model / data drift monitoring, and experiment tracking (W&B / MLflow).
  • Integration & interoperability : Embed AI into existing products and workflows via APIs, queues, SDKs, and webhooks with clear SLAs and observability.
  • Operate what you build : Instrument services, track p95 latency / availability / cost, and drive continuous improvement post-launch.
  • Mentor & uplift : Coach engineers on best practices (prompting, vector design, evals, latency / cost tuning, secure data handling).
  • Release cadence : Maintain monthly demo releases and production releases every two months with ALM-driven governance.
  • Ethical AI & compliance : Apply privacy-by-design, bias testing / mitigation, model cards, auditability, and data protection controls; ensure documentation in ALM.
  • Trendwatching : Track state-of-the-art AI (models, toolchains, infra) and pragmatically incorporate breakthroughs into roadmaps.

Qualifications :

  • 4 to 6 years delivering AI / ML features to production with fast POC ? MVP ? Production cycles.
  • Strong ML / DL fundamentals; hands-on with PyTorch and / or TensorFlow / Keras; LLMs (prompting, fine-tuning / LoRA), RAG patterns, and evaluation.
  • Python proficiency; scikit-learn, spaCy / NLTK; Hugging Face (Transformers / Datasets / PEFT); familiarity with YOLO / FastAI (role-relevant).
  • Backend engineering for production (FastAPI / Flask), auth, caching, testing; practical React / Next.js for demoable UIs.
  • MLOps : Docker / Kubernetes, CI / CD (GitHub Actions / Azure DevOps / Jenkins), experiment tracking (Weights & Biases / MLflow), monitoring Data & storage : SQL / NoSQL (Postgres, Redis), object stores; vector DBs (FAISS / Milvus / pgvector) and retrieval design.
  • Cloud : AWS / Azure / GCP with cost / latency / performance trade-off literacy.
  • AI productivity tools (required) : Cursor, Windsurf, Claude, Copilot for accelerated prototyping, code gen / review, and prompt workflows.
  • Effective communication; crisp documentation and governance in ALM.
  • Working knowledge of ethical AI and data protection (PII handling, access controls, audit trails).
  • (ref : hirist.tech)

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