Senior Software Engineer

7 days ago

Mumbai, India Vellstone Full time

We're hiring a Senior Software Engineer / Technical Lead for our product-based client to work on advanced AI and LLM-powered solutions. As a Senior Software Engineer / Technical Lead, your responsibilities would be: - Lead the design, development, and deployment of production-grade AI and LLM solutions using Python and Golang. - Architect and implement scalable backend services and REST APIs in Golang to serve AI/ML models with high performance. - Build and optimise RAG (Retrieval Augmented Generation) pipelines using vector databases and advanced retrieval strategies. - Design and implement sophisticated prompt engineering strategies (e.g., few-shot learning, chain-of-thought prompting, context optimisation) for LLM applications. - Work with major LLMs (e.g., GPT-4, Claude, Llama) to build intelligent systems for text generation, analysis, classification, and reasoning. - Develop microservices and data processing pipelines in Golang and Python to handle high-volume data ingestion, transformation, and model inference. - Build and maintain vector databases (e.g., Qdrant, Pinecone, Weaviate) for efficient similarity search and retrieval. - Optimize model performance, latency, and cost for production deployments across cloud environments. - Mentor junior team members and conduct code reviews. Requirements - 6+ years of experience in software engineering, data science, or AI/ML engineering roles. - Expert-level proficiency in Python with a deep understanding of modern libraries (Pandas, NumPy, FastAPI/Flask, asyncio). - Strong proficiency in Golang with experience building production-grade microservices, REST APIs, and concurrent systems. - Deep understanding of LLM architectures, capabilities, and limitations, with hands-on experience using platforms like OpenAI, Anthropic, or Hugging Face. - Proven expertise in prompt engineering techniques, including context management and optimization strategies. - Strong knowledge of RAG architectures, including chunking strategies, retrieval methods, and context management. - Deep understanding of embeddings (text, multimodal), vector databases, and semantic search principles. - Proficient in SQL with experience in database design, optimization, and working with both relational and vector databases. - Strong system design skills with the ability to architect scalable, fault-tolerant AI-powered applications. - Self-driven, with the ability to own projects end-to-end and deliver production-quality solutions. Benefits - You'll get to work with cutting-edge AI technologies, specifically leading the design and deployment of LLM-powered solutions. - Opportunity to leverage advanced skills in RAG systems, vector databases, and sophisticated prompt engineering. - Experience with model fine-tuning, evaluation, and A/B testing of AI systems is a plus. - Familiarity with orchestration frameworks like LangChain/Llamaindex and advanced prompting techniques (ReAct, Tree of Thoughts) is valuable. - Exposure to modern development and operations tools, including: - Model deployment/serving frameworks (vLLM, TGI, Triton). - Distributed systems and message queues (Kafka, RabbitMQ, Redis). - Cloud platforms (Kubernetes, Docker, AWS/GCP/Azure). - Monitoring/observability tools (LangSmith, Weights & Biases).

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