Consultant – AI

Skill: Consultant – AI
Exp: 4 to 7 years
Location: Hyderabad
Shift: Night Shift
As a Consultant, you contribute to technical delivery across modernization and cloud transformation projects. You work under the guidance of senior consultants and architects, applying strong hands‑on skills to implement solutions that align with established standards. You build subject‑matter expertise while strengthening delivery consistency and technical execution.
Responsibilities
Execute delivery tasks that support solution architectures and modernization priorities.
Implement application, data, or cloud components based on established technical designs.
Collaborate with team members across App Innovation, Cloud Platform, and Data & AI to ensure integrated delivery.
Follow delivery frameworks, coding standards, and quality checks established for the project.
Participate in design walkthroughs and apply feedback to improve technical execution.
Collaborate with architects, project managers, and client stakeholders to drive successful outcomes.
Support junior team members by sharing knowledge and best practices.
Support documentation, testing, and validation activities aligned to delivery needs.
Provide status updates, surface risks, and collaborate with leads to maintain execution quality.
Apply current Azure technologies and Microsoft frameworks to optimize solutions for maintainability, performance, and cost efficiency.
Contribute to reusable assets and internal frameworks as assigned.
Manage workload and commitments to meet utilization goals while maintaining architectural quality across engagements.
Invests in internal thought leadership, culture of feedback, knowledge-sharing, and/or Intellectual Property development opportunities, including communities of practice and internal initiatives.
Delivery and Consulting Excellence
Build trust with managers and product owners, influencing priorities and roadmaps in ways that support the client’s long-term interests.
Support effective Agile practices by ensuring a clear Definition of Done, and data-informed course corrections based on telemetry and feedback.
Demonstrated ability to leverage AI and emerging technologies to improve productivity, enhance decision-making, streamline delivery processes, and drive measurable business value. Commitment to continuous learning and adoption of new digital capabilities is required.
Requirements
Two years of experience delivering AI/ML or data solution components in one or two focus areas
Prior exposure to consulting or client-facing environments preferred
Proficiency in one or two of the following areas:
Agents & Orchestration – leveraging Semantic Kernel, LangChain, or similar frameworks to design intelligent workflows; applying tool/function calling, planner and agent-based patterns, and workflow automation engines
Search & Retrieval – implementing solutions with vector databases such as Azure AI Search, Pinecone, FAISS, or Milvus; applying hybrid search methods, re-ranking strategies, and selecting embedding models for accuracy and performance
Evaluation, Quality & LLM Operations – establishing offline and online evaluation approaches; using golden datasets, hallucination and groundedness validation, toxicity and safety testing; building telemetry and feedback loops; managing monitoring, deployment pipelines, and ongoing optimization of large language models
Responsible AI, Security & Privacy – incorporating practices such as threat modeling, privacy reviews, data minimization, safety guardrails, policy enforcement, auditability, and model risk management in line with GDPR and organizational standards
AI Platforms & Data Foundations – applying hands-on experience with Azure AI services, Databricks, Azure OpenAI, and related modern data platforms
Cloud Engineering – designing with APIs, containers, microservices, and DevOps pipelines to deliver scalable, cloud-native solutions
Data Integration & Governance – developing and managing data pipelines; applying quality controls, metadata practices, and master data management approaches
Analytics & Visualization – delivering insights with Power BI and other visualization tools
Familiarity with modern development tools (e.g., GitHub Copilot, Cursor)
Exposure to data engineering and governance concepts (data pipelines, quality, metadata)
Knowledge of analytics and data science tools (Python libraries, ML frameworks)
Relevant Azure or Databricks certifications in AI, Data, or Architecture
2 or more years of relevant experience implementing technical solutions on Azure
Technical foundation in one Azure domain (Application Innovation, Cloud Platform, or Data & AI)
Demonstrated ability to execute assigned tasks within application, cloud, or data domains
Experience working within delivery teams and following established technical processes with attention to detail
Effective communicator able to work collaboratively across project teams
Exposure to hybrid or multi-cloud environments is a plus.

Work arrangement
Hybrid