
Technical Architect
3 days ago
We are looking for a seasoned expert in Artificial Intelligence (AI) to join our team as a Technical Architect. This is an exciting opportunity to lead the development and implementation of AI-based applications using cutting-edge technologies like Large Language Models (LLMs).
As a Technical Lead, you will be responsible for architecting and implementing LLM pipelines that include prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation. You will also design scalable microservices and APIs for AI features and collaborate with MLOps teams to deploy and monitor AI models in production.
In addition to your technical expertise, you will guide the team on Python best practices, code reviews, and technical problem-solving. You will stay updated on emerging AI/LLM advancements and propose adoption where beneficial.
Responsibilities- Lead the development and integration of Python-based applications with LLMs (OpenAI, DeepSeek, Anthropic, LLaMA, etc.).
- Architect and implement LLM pipelines including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and evaluation.
- Design scalable microservices and APIs for AI features.
- Collaborate with MLOps teams to deploy and monitor AI models in production.
- Ensure performance optimization, cost efficiency, and security in LLM workflows.
- Guide the team on Python best practices, code reviews, and technical problem-solving.
- Stay updated on emerging AI/LLM advancements and propose adoption where beneficial.
- Strong proficiency in Python (FastAPI, Flask).
- Solid experience with LLM integration (OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex).
- Understanding of RAG pipelines (vector databases like Pinecone, Weaviate, FAISS, Milvus).
- Experience with prompt engineering & evaluation techniques. Knowledge of MLOps tools (MLflow, Kubeflow, Langfuse) and deployment on AWS/GCP/Azure.
- Familiarity with containerization and orchestration (Docker, Kubernetes).
- Strong grasp of REST APIs, GraphQL, and microservices architecture. Knowledge of model fine-tuning and performance optimization.
- Opportunity to work with cutting-edge AI technologies.
- Collaborative and dynamic work environment.
- Professional growth and development opportunities.
- Competitive salary and benefits package.
- Excellent leadership and mentoring abilities.
- Effective communication with technical and non-technical stakeholders.
- Ability to work in a fast-paced, evolving AI environment.
- Experience with agentic AI or Model Context Protocol (MCP). Background in data pipelines (ETL, streaming data).
- Exposure to AI security & compliance practices. Prior work in scalable enterprise AI products.
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