AI Full Stack Engineer

Job Description

Job Responsibilities :

– AI Application Development : Design and build production-grade Generative AI and multi agent systems.

– AI Orchestration : Implement orchestration using LangChain, LangGraph, LlamaIndex, Semantic Kernel, n8n, or custom frameworks.

– LLM Integration : Integrate GPT, Claude, Gemini, and self hosted/open source LLMs.

– RAG Pipelines : Implement Retrieval-Augmented Generation using Pinecone, ChromaDB, Weaviate, pgvector.

– Hybrid Retrieval : Build BM25 + semantic search architectures using ElasticSearch or Solr.

– Prompt Engineering : Develop prompt and context optimization strategies for accuracy, latency, and cost reduction.

– LLM Guardrails : Implement evaluation pipelines, monitoring, observability, and safety checks for LLM systems.

– Multimodal Workflows : Build AI workflows involving text, image, audio, and video modalities.

– Fullstack Frontend : Develop modern front-end applications using React/Next.js, TypeScript, HTML, CSS.

– Backend Engineering : Build modular backend services in Python, JavaScript, or Java.

– Clean Architecture : Apply DDD, SOLID principles, and clean architecture patterns.

– Database Expertise : Work with relational, document, graph, and key value databases.

– Auth Systems : Implement secure OAuth2.0, OIDC, and JWT based authentication.

– SSO Integrations : Integrate Google, Azure AD, Okta, Auth0, Cognito, or enterprise IdPs.

– Event Architectures : Implement event-driven systems using Kafka, MSK, SQS, or equivalents.

– AI Assisted Development : Use tools like Claude Code, GitHub Copilot, Cursor, Codex in structured workflows.

– Workflow Standardization : Build standardized AI-assisted coding workflows and sub agent patterns.

– Innovation Leadership : Lead PoCs, internal R&D, and innovation initiatives.

– Team Mentoring : Mentor engineers in AI system design and best practices.

– Tech Awareness : Stay current with emerging AI models, frameworks, and production trends.

What We are Looking For :

– An engineer who can build end- to- end AI- powered fullstack products, not just prototypes.

– Someone strong in LLM engineering, RAG pipelines, orchestration, and scalable system design.

– A fullstack builder with strong fundamentals in frontend, backend, and cloud-native systems.

– A believer in clean architecture, modular design, and high- quality engineering practices.

– Someone who understands performance, observability, security, and cost-efficient AI deployment.

– A collaborator who works closely with Product, ML, Design, and Platform teams.

– A senior engineer with ownership mindset, architectural depth, and strong mentoring skills.

Skills Set Required :

– 6+ years of software development experience.

– Minimum 2 years of hands- on experience in AI/ML or Generative AI.

– Proven experience deploying production-grade LLM or GenAI systems.

– Strong understanding of LLM internals, prompting, and context optimization.

– Experience building RAG pipelines and using vector databases.

– Strong proficiency in Python, JavaScript, FastAPI, GraphQL.

– Experience with Docker, Kubernetes, and CI/CD pipelines.

– Experience with cloud-native deployments (AWS / GCP / Azure).

– Strong knowledge of scalable microservices and distributed systems.

Bonus : Experience building multi- agent/autonomous systems, Bachelor’s or Masters in CS or equivalent.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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