About the Role
We design and develop enterprise software and artificial intelligence solutions. We’re looking for a Senior AI Engineer who can play a decisive role in defining architecture, selecting technologies, developing, and operationalizing intelligent capabilities across our products.
Beyond hands-on development, this role involves problem analysis, architectural decision-making, model quality evaluation, knowledge transfer, and technical leadership of AI projects.
Key Responsibilities:
Break down complex business problems into well-defined, AI-solvable tasks.
Design end-to-end architectures for AI/ML solutions in enterprise products.
Select the right models, methods, tooling, and infrastructure—balancing accuracy, cost, latency, security, and scalability.
Design and build solutions powered by Large Language Models (LLMs) and Generative AI.
Provide technical leadership for projects involving RAG, semantic search, NLP, information extraction, and intelligent agents.
Design evaluation, monitoring, and quality-control methodologies for model outputs.
Perform error analysis and design mitigation strategies to reduce hallucinations and keep responses reliable.
Productionize prototypes into stable, maintainable, product-ready services.
Collaborate with software, product, data, and business teams to define and prioritize intelligent capabilities.
Define technical standards for model development, testing, deployment, and documentation.
Monitor AI service performance and cost; propose and implement optimizations.
Contribute to MLOps processes and production model monitoring.
Conduct code reviews, technical design reviews, and review team outputs.
Transfer knowledge and help Junior and Mid-Level engineers grow.
Track emerging technologies and research; assess their applicability to enterprise products.
Present technical solutions to product teams, management, and enterprise clients.
Required Skills & Experience:
Ph.D. or Master’s degree in AI, Computer Science, Computer/Electrical Engineering, Math, Statistics, or a related field.
Minimum 5 years of professional experience in AI/ML, NLP, or data science.
Proven track record of designing and shipping AI projects in production.
Strong Python skills and fluency with common ML/DL libraries and frameworks.
Practical proficiency with PyTorch or TensorFlow.
Expertise in the following areas is a must:
Agentic AI—designing, orchestrating, and evaluating intelligent agents.
LLMs—working hands-on with large language models and Generative AI.
STT (Speech-to-Text) and TTS (Text-to-Speech)—building voice capabilities.
RAG design patterns—advanced retrieval-augmented generation, hybrid/agentic RAG.
Embeddings & Vector Databases.
Prompt engineering & fine-tuning pre-trained models.
LLM evaluation and test-set design.
Error control, hallucination mitigation, and response quality.
Additional Technical Expectations:
Ability to design APIs and AI services for use within software products.
Experience with Docker, Git, and Linux.
Familiarity with microservice architecture and production AI service deployment.
MLOps tooling and workflows (a plus).
Ability to reason through accuracy/speed/cost/complexity trade-offs.
Ability to document technical decisions and present them to technical and non-technical audiences.
Strong capacity for technical leadership and cross-team collaboration.
Advantageous / Nice-to-Have:
Experience building intelligent assistants, enterprise chatbots, or intelligent search systems.
Work with unstructured text, documents, and organizational knowledge.
Experience with open-source LLMs and cloud AI services.
Experience with vector databases and search engines.
Experience designing intelligent systems used by enterprise customers.
Publications, open-source contributions, or professional portfolio projects.
Familiarity with data security, privacy, and responsible AI practices in organizations.