Lead AI Engineer

Company Description Vector & Voice Technologies is a technology studio that builds high-reliability software rails, autonomous AI agents, and enterprise data retrieval architectures to remove operational friction for businesses. The team focuses on high-utility, lightweight, production-grade systems instead of generic, bloated software suites. Their work spans conversational messaging interfaces, real-time queue orchestration engines, and intelligent knowledge pipelines integrated into existing enterprise workflows. Based in Thiruvananthapuram, the company combines practical field utility with modern computational infrastructure to help organizations automate workflows, reduce overhead, and deliver smoother customer experiences. Core capabilities include autonomous AI agents and chat automation, enterprise knowledge systems using RAG and vector search, real-time operational infrastructure, and custom enterprise integrations.
Role Description The Lead AI Engineer will design, build, and optimize production-grade AI systems, with a focus on autonomous agents, NLP-powered workflows, and retrieval-augmented generation pipelines. Day-to-day responsibilities include architecting and implementing neural network–based models, designing data pipelines and vector search infrastructure, integrating AI components with existing enterprise systems and APIs, and overseeing deployment on robust, fault-tolerant rails. The role involves leading technical design discussions, reviewing code, mentoring other engineers, and collaborating closely with product and operations teams to translate real-world constraints into practical AI solutions. This is a full-time, on-site role based in Thiruvananthapuram.
Qualifications
Strong foundation in Computer Science and Software Development, including data structures, algorithms, distributed systems, and production-grade coding practices.
Expertise in Neural Networks and Pattern Recognition, with experience training, evaluating, and deploying models for real-world applications.
Hands-on experience with Natural Language Processing (NLP), including conversational agents, RAG pipelines, and text processing over unstructured data.
Proficiency with modern AI/ML tools and frameworks (e.g., Python, PyTorch or TensorFlow, vector databases, orchestration frameworks) and cloud or container-based deployment environments.
Proven ability to architect end-to-end AI solutions: data ingestion, model design, evaluation, monitoring, and lifecycle management in production.
Comfort working closely with cross-functional stakeholders to understand operational workflows and translate them into robust technical designs.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
Experience leading engineering teams or serving as a technical lead on complex AI or data infrastructure projects is highly beneficial.

Work arrangement
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