Generative AI Architect

Company Overview: -

• Mid-Sized Pioneering IT and Engineering Services Company
• Domains: Hi-Tech, Automotive, Manufacturing, Telecom, Medical and Life Sciences, Pharmaceutical
• Successfully service Fortune 500 Companies
• Customer Geographies: North America, Europe, Japan, Korea, China

Job Description: GenAI Architect for Our AI/ML Leadership Team

ABOUT THE ROLE:

We are looking for an experienced Generative AI Architect to join our AI/ML Leadership team and work in close, direct partnership with CXOs to scale AI capabilities from its current maturity to a significantly larger order of impact. The successful candidate in this high visibility role will be expected to design, build, and defend GenAI-based solutions end-to-end, on Microsoft Azure, while operating with a high degree of autonomy and technical accountability. The role expects substantial overlap with European working hours to support direct, real-time engagement with Customer leadership/stakeholders.

The candidate will regularly present architecture and design decisions directly to Customers CTO and Engineering Leadership stakeholders, and must be able to justify those decisions rigorously, respond to challenge with sound reasoning, and constructively challenge prevailing perspectives where the evidence supports it and hence the role demands more than technical depth. Strong communication and the ability to defend one's work under scrutiny are treated as core competencies for this position equal in importance to technical execution.

Expected Candidate Experience For This Role:

The ideal candidate will bring 8 to 10 years of overall experience in software development, with a substantial and demonstrable portion of that experience focused on AI/ML and Generative AI technologies. A higher level of experience is a meaningful factor in this role and is expected to have translated into genuine seniority — specifically, the ability to execute independently, defend technical work under scrutiny, justify design choices with sound reasoning, and constructively challenge perspectives, including those of senior stakeholders. Candidates whose experience has developed these capabilities will be given added weight in evaluation.

KEY RESPONSIBILITIES:

• Candidate should be excited / comfortable working in a fast-paced, collaborative environment and will be expected to engage regularly and directly with senior technical leadership. Inclination to work in integrated environments as an extended team of the Customer and carry oneself as a techno-functional expert and stay in constant liaison with internal leadership will be a primary trait of the candidate.
• This role involves working as an extension of the customer's engineering team, embedded within their environment and reporting lines for day-to-day execution, while maintaining a strong connection with our internal leadership.
• Design, develop, and deploy GenAI-driven applications on Microsoft Azure to address complex, real-world business problems.
• Implement Retrieval-Augmented Generation (RAG), Retrieval-Interleaved Generation (RIG), and Agentic Frameworks.
• Take end-to-end ownership of solution architecture, from design through deployment, and be accountable for the reasoning behind each design choice.
• Design and optimize document chunking strategies tailored to specific datasets and use cases.
• Build, manage, and optimize data embeddings for high-performance similarity search across vector databases.
• Present architecture, design trade-offs, and technical recommendations directly to the CTO and cross-functional leadership.
• Defend design and implementation choices with clear, evidence-based reasoning, and respond constructively to challenge.
• Proactively challenge existing approaches and assumptions where a better-reasoned alternative exists, while remaining open to being persuaded otherwise.
• Mentor and raise the technical bar for less experienced members of the team.
• Work closely with data engineers and data scientists to integrate AI solutions into existing pipelines.
• Collaborate with cross-functional teams to ensure seamless AI implementation.
• Utilize Microsoft Azure OpenAI Service, Azure AI Search, and Azure AI Foundry / Azure Machine Learning as the primary platforms for solution delivery.
• Explore and implement best practices for Azure-native AI architecture; familiarity with Amazon Bedrock and other cloud-native AI platforms is an advantage.
• Stay current with emerging trends and technologies in GenAI and AI/ML, ensuring solutions remain state-of-the-art.
• Perform exploratory data analysis (EDA) and data pre-processing to serve the data modeling layer.
• Perform technical benchmarking of GenAI models using evaluation metrics and validation approaches.
• Build agentic workflows using RAG and LLMs.
• Build and maintain scalable data pipelines to ingest data/metadata/signals from websites, structured and unstructured content sources.
• Design and implement embeddings for retrieval/RAG.
• Develop candidate generation solutions using vector embeddings, hybrid retrieval techniques, and ANN search.
• Develop and maintain APIs for integration with multiple applications and digital platforms.
• Train, validate, deploy, and monitor GenAI pipelines using established LLMOps practices, model registries, and automated deployment pipelines.
• Implement scalable vector database solutions to support semantic search and embedding-based retrieval.
• Monitor model performance, hallucination rate, faithfulness, grounded-ness, prompt regression to maintain model effectiveness.
• Support A/B testing, experimentation, and continuous optimization by analyzing user feedback.
• Collaborate with data engineers, software engineers, product managers, and business stakeholders to deliver production-ready AI and GenAI solutions.
• Ensure compliance with data governance, privacy, security, & organization standards in GenAI workflows.
• Contribute to CI/CD pipelines, infrastructure automation, technical documentation, engineering best practices.
• Mentor junior team members through technical guidance, code reviews, and knowledge sharing

REQUIRED QUALIFICATIONS:

• 8 to 10 years of overall experience in software development, with significant experience focused on AI/ML.
• Bachelor's Degree (Masters preferred) in CS/IS/AI/ML preferably from top engineering institutes
• Substantial hands-on experience with Generative AI (GenAI) technologies.
• Strong working knowledge of Python, PySpark, and SQL.
• Demonstrated ability to execute independently, defend design decisions, and communicate technical reasoning clearly to senior, non-technical, and technical stakeholders alike.
• Proven ability to work in a collaborative, fast-paced, and innovative environment.
• Proficiency in FastAPI, Celery, and Keycloak.
• Exposure to Microsoft O365 tools.
• Experience with distributed data processing frameworks such as Apache Spark or Databricks.
• Knowledge of MLOps, LLMOps, model deployment, experiment tracking, model versioning, monitoring.
• Understanding of REST APIs, scalable inference services, and cloud-native application architectures.
• Experience leveraging knowledge graphs, taxonomies, and vector embeddings to enhance semantic retrieval, and Retrieval-Augmented Generation (RAG) solutions.
• Expertise in Generative AI frameworks, including prompt engineering, fine-tuning, and few-shot learning.
• Familiarity with frameworks such as LangChain, LangGraph, T5 (Text-to-Text Transfer Transformation), and open-source stacks including Ollama, Mixtral, and DeepSeek.
• Strong knowledge of RAG for combining LLMs with external data retrieval systems.
• Experience designing chunking strategies for different datasets and use cases.
• Expertise in data embedding techniques and experience with vector databases, including Azure AI Search, Pinecone, and ChromaDB.
• Strong programming skills in Python.
• Experience with AI/ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Strong, hands-on experience with Microsoft Azure for AI/ML workloads, including Azure OpenAI Service, Azure AI Search, and Azure AI Foundry / Azure Machine Learning.
• Experience with API integration for AI services and building scalable applications.

PREFERRED QUALIFICATIONS:

• Certification in AI/ML on Microsoft Azure or equivalent.
• Certification or coursework in Generative AI or related technologies.
• Familiarity with Amazon Bedrock and other cloud-native AI platforms is an advantage.
• Experience with taxonomy management, knowledge graphs, or ontology-based systems.
• Knowledge of IaC (Terraform) & containerization technologies such as Docker and Kubernetes.
• Exposure to enterprise-scale cloud-native AI solutions.
• Relevant cloud platform or machine learning certifications are an added advantage.

WHAT WE OFFER:

• Awesome Culture: Creative Synergies has a flat organization and an agile culture of positivity, entrepreneurial spirit, customer centricity, celebrating technical excellence, teamwork, and meritocracy
• Opportunity to work with Customers who are technology Leaders (including Global Fortune 500 Customers) & work on Real-World Problems that matter and are often mission-critical
• Leadership role with significant influence over AI strategy and team direction.
• Access to state-of-the-art GPU infrastructure and cutting-edge AI tools.
• Competitive compensation package with performance-based incentives.
• Flexible working arrangements with hybrid options.
• Continuous learning budget for conferences, courses, and certifications.