Note: The job is a remote job and is open to candidates in USA. Vanigent is seeking a highly experienced Senior Software Engineering Lead to drive the design, development, and deployment of advanced artificial intelligence solutions across the organization. This role involves leading AI strategy execution, building production-ready AI systems, and managing a team of AI and software developers.
Responsibilities
- Lead the research, design, and implementation of AI and machine learning solutions aligned with business priorities
- Provide technical direction for AI architecture, model selection, AI infrastructure, and production deployment
- Evaluate emerging AI technologies, foundation models, agentic frameworks, and infrastructure tools to determine suitability for company use
- Define technical standards, best practices, and governance for AI development, deployment, monitoring, and responsible use
- Partner with product, engineering, data, and business leaders to identify high-value AI opportunities and translate them into executable roadmaps
- Design and build custom AI products, including predictive models, RAG pipelines, agentic AI workflows, semantic search systems, and fine-tuned models
- Develop AI-powered features and services that integrate with existing platforms, workflows, and business systems
- Build and optimize LLM-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, OpenAI SDK, Anthropic SDK, and Model Context Protocol or MCP
- Design embedding pipelines, vector database structures, hybrid search, re-ranking, and graph-augmented retrieval solutions
- Lead development of multimodal AI solutions involving text, image, audio, structured data, and other domain-specific inputs
- Lead deployment, monitoring, versioning, and continuous improvement of AI models in production environments
- Build and maintain MLOps pipelines for model training, evaluation, deployment, retraining, and lifecycle management
- Ensure AI systems are scalable, reliable, secure, explainable, and aligned with business and compliance requirements
- Oversee cloud-based AI workloads on AWS, GCP, or Azure, including GPU and TPU infrastructure where applicable
- Establish standards for model performance monitoring, data drift detection, cost optimization, and production reliability
- Directly manage AI and software developers, including hiring support, onboarding, performance management, mentoring, workload prioritization, and career development
- Provide coaching and technical guidance to junior, mid-level, and senior developers
- Promote a culture of technical excellence, accountability, continuous learning, innovation, and responsible AI development
- Review technical output, ensure code quality, support architecture decisions, and remove blockers for the team
- Work closely with leadership to align team capacity, priorities, and deliverables with company objectives
Skills
- Software Development 5+ years
- AI / ML Engineering in Production 3+ years
- LLM / Generative AI Development 2+ years
- Cloud AI Deployment 2+ years
- MLOps / Model Lifecycle Management 2+ years
- People Management / Technical Leadership 2+ years
- Strong proficiency in Python and working knowledge of TypeScript or JavaScript for AI system integration
- Strong experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers
- Hands-on experience with RAG architecture, embeddings, semantic search, vector databases, hybrid retrieval, re-ranking, and graph-augmented retrieval
- Experience with LangChain, LangGraph, LlamaIndex, OpenAI SDK, Anthropic SDK, and Model Context Protocol or MCP
- Experience with vector databases such as Pinecone, Weaviate, pgvector, ChromaDB, or Qdrant
- Experience with fine-tuning techniques such as LoRA, QLoRA, RLHF, and DPO
- Strong understanding of MLOps, CI/CD, Docker, Kubernetes, model serving, monitoring, and model versioning
- Experience with cloud platforms such as AWS, GCP, or Azure, including scalable AI and ML workloads
- Strong knowledge of databases, data pipelines, SQL, NoSQL, preprocessing, testing, Git, code review, and software engineering best practices
- Strong strategic thinking and ability to translate business goals into AI solutions
- Ability to lead technical teams, manage priorities, and deliver results in a fast-moving environment
- Strong communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders
- High accountability, sound judgment, resilience, curiosity, and commitment to continuous improvement
- Ability to evaluate trade-offs involving performance, cost, risk, scalability, compliance, and user impact
- Experience with agentic AI frameworks such as AutoGen, CrewAI, OpenAI Agents SDK, Anthropic Claude Agent SDK, and MCP server development
- Background in NLP, computer vision, multimodal AI, or applied AI product development
- Published research, open-source contributions, patents, or strong AI project portfolio
- Experience with A/B testing, model monitoring, data drift detection, responsible AI, AI safety, model explainability, SHAP, LIME, and AI governance frameworks
- Relevant certifications such as AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, DeepLearning.AI certifications, or similar AI/ML credentials
Company Overview