AI Software Engineer (LLM & Full-Stack Systems)
 

About the Role

• We are seeking an end-to-end AI Software Engineer who is equally strong in engineering and applied AI, someone who can fine-tune models, build scalable AI agents, and ship & manage production-grade applications.
• The ideal candidate has built and deployed LLM-powered systems that serve real users, handling everything from prompt orchestration and fine-tuning to inference optimization, caching, latency reduction, logging, monitoring, and post-deployment model evaluation.
   
• You’ll work closely with our AI, product, and infrastructure teams to deliver high-performance, secure, and scalable AI applications across web and enterprise environments.

 

Key Responsibilities

1. Generative AI Engineering

• Fine-tune, quantize, and deploy open-source LLMs (e.g., Llama-3, Mistral, Falcon, DeepSeek, Phi, etc.) for specific domains and clients
• Build and maintain multi-agent orchestration systems using frameworks like LangChain, LlamaIndex, or custom Python pipelines.
• Create and maintain retrieval-augmented generation (RAG) pipelines with vector databases (Qdrant, Pinecone, Weaviate, FAISS).
• Create architectures for different AI services, optimize prompt templates, context windows, and chain execution for efficiency and precision.
• Integrate and evaluate speech, vision, and multimodal models for production-ready use cases.

 

2. LLM Platform Management & Production Operations

• Deploy and maintain LLM inference servers (vLLM, Ollama, TGI, or custom microservices).
• Apply prompt caching, embedding pre-computation, and batch inference for performance optimization.
• Evaluate model performance and quality using automated feedback loops and analytics dashboards.

 

3. Full-Stack & Systems Development

• Architect, develop, and maintain frontend interfaces (React / Next.js) and backend services (FastAPI / Node.js).
• Design robust REST / GraphQL APIs for interaction with AI microservices.
• Integrate vector databases, relational DBs, and cloud storage in scalable data architectures.
• Contribute to both rapid prototyping (Streamlit / Gradio) and enterprise-grade platforms.

 

4. Collaboration & Product Development

• Work cross-functionally with AI researchers, product designers, and cloud architects to deliver complete user experiences.
• Participate in technical planning, code reviews, and performance audits.
• Document internal tools, APIs, and best practices for future developers.
• Contribute to architectural decisions for scalability, cost optimization, and compliance.

Required Skills & ExperienceLanguages: Python, TypeScript/JavaScript, SQL, Bash.Frameworks: FastAPI, Flask, Django, React, Next.js, LangChain, LlamaIndex.Databases: PostgreSQL, MongoDB, Redis, Qdrant, Pinecone.AI & ML Stack: PyTorch, Transformers, Hugging Face, vLLM, Ollama, OpenAI SDK.DevOps & Cloud: Docker, Kubernetes, GCP, GitHub Actions, Terraform.Observability: Prometheus, Grafana, OpenTelemetry, Sentry, ELK stack.Preferred Add-ons: Experience with edge inference, GPU orchestration, or local on-prem deployments. QualificationsExperience RequiredMinimum 4–5 years of professional experience in software development, including hands-on work with Generative AI applications in production environments. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field.Proven experience in building and scaling AI-powered applications in production.Demonstrated ability to own the full lifecycle — from ideation to deployment and monitoring. Soft SkillsOwnership mentality and strong debugging instincts.Ability to design clean architectures and maintain production-grade code.Deep curiosity for emerging AI trends and optimization methods.Excellent communication, documentation, and collaboration skills.