Senior Software Engineer

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).