Unison Group
AI Solution Architect
- Compensation
- Not disclosed
- Location
- Hyderabad, Telangana, India
- Work setup
- Not specified
- Seniority
- C level
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Architecture
- Posted
Skills
Must have
- AI Strategy & Leadership
- • Define and own AI strategy and multi-year roadmaps aligned to client and C-level business priorities, with clear value metrics (revenue, cost, risk, productivity).
- • Lead the full AI/ML product lifecycle: opportunity discovery, business case, architecture, build, deployment, adoption and value tracking.
- • Build, mentor and lead agile delivery teams spanning data scientists, ML/MLOps engineers, data engineers and product managers.
- • Act as a trusted advisor to executives, translating complex technical options into clear decisions on investment, risk and trade-offs.
- Solution Architecture & Delivery
- • Architect enterprise-grade, cloud-native AI/ML and analytics platforms on Azure (ADF, Azure ML, Synapse, Event Hubs, Key Vault) and Databricks.
- • Design and deliver GenAI and agentic AI solutions: LLM integrations (OpenAI and others), retrieval-augmented generation (RAG), vector databases (e.g. Milvus), prompt engineering, memory-enabled agen
- • Establish MLOps foundations using MLflow, Docker, Kubernetes and Terraform for reproducible training, CI/CD, monitoring and scalable model serving.
- • Set architecture standards, reference designs and reusable components that reduce time-to-production across engagements.
- • Guide data and analytics solutions end to end, from pipelines (Python, SQL, PySpark) to optimisation (Gurobi) and BI dashboards (Power BI, Tableau, Spotfire, Qlik).
- Responsible AI & Governance
- • Define and embed Responsible AI practices: fairness, explainability, privacy, security, model risk management and human oversight.
Nice to have
- • Certifications such as Azure Solutions Architect Expert, Azure AI Engineer, Databricks ML Professional or TOGAF.
- • Experience with AWS or GCP AI services, or multi-cloud architectures.
- • Industry exposure in financial services, energy, healthcare, manufacturing or the public sector.
- • Experience designing or delivering AI training and enablement content.
- SUCCESS IN THE FIRST 12 MONTHS
- • An agreed AI roadmap and reference architecture adopted across key client engagements.
- • At least two GenAI or ML solutions in production with tracked business value.
- • A working Responsible AI and MLOps framework reused by delivery teams.
- • A high-performing, cross-functional team and a strong bench of client executive relationships.
- Reports to: Chief Executive Officer / Head of AI
Full description
ROLE SUMMARY: We are looking for an AI Solution Architect who can take an enterprise AI initiative from vision to execution. You will shape AI strategy with C-level stakeholders, architect cloud-native GenAI and ML platforms on Azure and Databricks, and lead cross-functional teams across data science, MLOps and product engineering to deliver them. You are equally comfortable presenting a roadmap to a board, reviewing a RAG pipeline design and coaching an engineer through a production incident.
Experience
- 12+ years in data, analytics or software engineering, including 5+ years leading AI/ML platforms or products in an enterprise setting.
- Proven record of taking ML and GenAI solutions into production at scale, with measurable business impact.
- Hands-on delivery of at least one production LLM/RAG solution, plus hands-on experience with agentic AI patterns.
- Experience leading multidisciplinary teams and presenting to C-level executives.
- Bachelor's or master's degree in computer science, Data Science, Engineering, Statistics or a related field.
Cloud & MLOps: Azure (ADF, Azure ML, Synapse, Event Hubs, Key Vault), Databricks, Kubernetes, Docker, Terraform, CI/CD
Data & ML: Python, SQL, PySpark, MLflow, TensorFlow, Gurobi, Dataiku, SAS, Alteryx
GenAI & Agentic AI: OpenAI and other LLMs, LangChain, Milvus / vector databases, RAG, prompt engineering, memory agents, NLP, LLM evaluation
BI & Visualisation: Power BI, Tableau, Spotfire, Qlik
Leadership Competencies:
- AI strategy and roadmap execution
- AI/ML product lifecycle management
- Responsible AI and governance
- Stakeholder engagement and executive communication
- Training, change management and AI adoption
- Cross-functional team leadership
- Vendor and partner collaboration
Nice to Have
- Certifications such as Azure Solutions Architect Expert, Azure AI Engineer, Databricks ML Professional or TOGAF.
- Experience with AWS or GCP AI services, or multi-cloud architectures.
- Industry exposure in financial services, energy, healthcare, manufacturing or the public sector.
- Experience designing or delivering AI training and enablement content.
SUCCESS IN THE FIRST 12 MONTHS
- An agreed AI roadmap and reference architecture adopted across key client engagements.