Novac Technology Solutions is a leading digital transformation and technology services provider, delivering innovative software products and solutions across industries. With strong expertise in insurance, finance and digital ecosystems, we empower clients with future-ready technologies and business excellence.
Role Overview:
As an AI Architect, you will play a critical technical leadership role, responsible for designing and delivering enterprise-grade AI solutions. You will serve as a technical lead for strategic AI initiatives, providing hands-on expertise across Generative AI and Agentic AI solutions. Additionally, you will support the growth and upskilling of the AI & Data team through coaching and mentorship.
What You Will Do:
- Architect and implement enterprise-grade AI solutions by collaborating with senior leadership to define technology strategies aligned with business objectives.
- Serve as a technical leader for strategic AI initiatives, guiding solution design decisions across architecture, platforms, and implementation approaches.
- Support and advance AI Studio capabilities, including reusable architectures, accelerators, best practices, and reference implementations.
- Lead the design and development of AI platforms, including model lifecycle management, cloud-native deployment pipelines, MLOps, and scalable agentic architectures.
- Architect and build AI platforms and pipelines leveraging cloud-native services (AWS, Azure, GCP) to support model development, deployment, monitoring, and governance.
- Drive hands-on development of Generative AI and Agentic AI solutions, including LLM-based systems, retrieval-augmented generation (RAG), and multi-agent architectures.
- Evaluate and integrate emerging AI technologies and frameworks, assessing their applicability to business and internal use cases.
- Provide technical leadership, coaching, and mentorship to AI engineers and junior team members, fostering growth and skill development.
- Promote a culture of engineering excellence, innovation, and responsible AI, ensuring solutions adhere to data governance, security, and ethical standards.
What You Will Need:
- Bachelor's or master's degree in Computer Science, Engineering, Data Science, or a related field.
- Overall 12+ years of experience, with strong expertise in AI, machine learning, or data analytics, with a strong focus on solution architecture and deployment.
- Minimum of 2 years of hands-on experience with Generative AI and/or Agentic AI architectures and solutions.
- Proven experience designing and deploying AI solutions on cloud platforms such as AWS, Azure, Google Cloud, Palantir, or Databricks.
- Strong understanding of big data technologies, AI frameworks, and modern cloud ecosystems.
- Hands-on experience and demonstrated leadership in developing applications, data pipelines, and cloud-native AI solutions.
- Excellent communication and collaboration skills, with the ability to influence technical direction and work effectively with global stakeholders.
- Strategic mindset with a passion for innovation and continuous improvement.
What Would Be Nice to Have:
- Strong foundation in machine learning: supervised and unsupervised learning, classification, regression, clustering, ensemble methods, and evaluation techniques.
- Hands-on deep learning experience: CNNs, RNNs/LSTMs, Transformers, and attention mechanisms.
- Proficiency in Python for ML: NumPy, pandas, scikit-learn, and frameworks such as PyTorch or TensorFlow.
- Understanding of NLP: tokenization, embeddings, text classification, named entity recognition, and sequence-to-sequence models.
- Knowledge of neural network optimization techniques: gradient descent variants, regularization (dropout, batch normalization), hyperparameter tuning.
- Familiarity with reinforcement learning concepts and their applications to LLMs and Generative AI.
- Experience integrating LLMs (GPT, Claude, Gemini, LLaMA, Mistral) into applications.
- Prompt engineering skills: zero-shot, few-shot, chain-of-thought, ReAct, and structured output patterns.
- Experience building RAG systems: document chunking, embedding models, vector search, and retrieval optimization.
- Working knowledge of AI/LLM orchestration frameworks (LangChain, LlamaIndex, LangGraph, or similar).
- Understanding of AI agent patterns, tool use, and agentic workflows.
- Strong software engineering fundamentals: clean code, design patterns, API development, testing practices.
- Experience building and deploying production services (RESTful APIs, microservices).
- Familiarity with Docker, CI/CD pipelines, and Git-based workflows.
- Working knowledge of databases (SQL and NoSQL) and vector databases.
What We Offer
- An exciting opportunity to be part of a leading FinTech product company.
- The chance to work within a vibrant team and develop your career in the BFSI domain.
- A multifaceted role with significant responsibility and a broad spectrum of opportunities.
- Access to professional education and personal development programs.
