Solutions Architect

Accountabilities: Lead client discovery sessions to understand business objectives, technical requirements, constraints, and desired outcomes. Translate complex client challenges into scalable, secure, and production-ready Data & AI architectures. Serve as the primary technical advisor throughout client engagements, providing guidance on architecture, tooling, implementation approaches, and technical trade-offs. Develop architecture diagrams, technical design documentation, implementation plans, standards, and other materials required to support successful delivery. Lead enterprise Data & AI solutions from initial architecture through implementation and production deployment. Guide engineering teams through technical implementation while identifying risks, resolving architectural challenges, and removing delivery blockers. Apply AI throughout the software delivery lifecycle to improve solution design, engineering productivity, code quality, testing, documentation, troubleshooting, and client outcomes. Advise clients on practical approaches to adopting AI within their engineering and data environments. Mentor engineers through architectural guidance, technical coaching, design reviews, and knowledge sharing. Contribute to technical hiring, onboarding, enablement, and the development of engineering capabilities. Communicate complex technical concepts and architectural decisions clearly to engineering teams, technical leaders, and executive stakeholders. Operate effectively across distributed teams and time zones while maintaining strong collaboration and delivery standards. Requirements 8+ years of experience in Solutions Architecture, Data Engineering, technical consulting, or a related field. Proven experience designing and delivering enterprise Data & AI solutions into production within cloud environments. Demonstrated experience using modern AI technologies throughout the software delivery lifecycle to improve solution design, engineering productivity, code quality, testing, documentation, troubleshooting, and client outcomes. Strong consulting experience leading technical discovery, solution architecture, and client-facing engagements. Hands-on experience with several modern cloud and data platforms, such as Snowflake, Databricks, Google BigQuery, AWS, Microsoft Azure, and Google Cloud Platform. Strong experience with data engineering technologies such as Python, SQL, Java and/or Scala, Spark, Kafka, Airflow, dbt, Fivetran, Matillion, or comparable technologies. Experience with modern engineering practices, including CI/CD, Infrastructure as Code, observability, and monitoring. Practical experience incorporating AI into engineering and solution delivery using technologies such as Anthropic Claude, OpenAI, GitHub Copilot, Microsoft Copilot, Google Gemini, Snowflake Cortex AI, AWS Bedrock, LangChain, LangGraph, or similar enterprise AI platforms and frameworks. Strong communication, consulting, and stakeholder-management skills, with the ability to engage effectively with both technical and executive audiences. Ability to navigate ambiguity, make sound architectural decisions, and communicate technical trade-offs clearly. Experience mentoring engineers and providing technical leadership within distributed or global teams. Industry certifications across Snowflake, AWS, Azure, GCP, Anthropic, and/or Databricks are a plus. Contributions to technical communities through speaking, writing, open-source projects, or internal technical enablement are advantageous. Benefits Remote-first workplace with the opportunity to work from India. Medical insurance coverage for employees and their families. Medical insurance coverage for parents. Term life and personal accident insurance. Wellness allowance. Broadband/internet reimbursement. Continuous learning and professional development opportunities. Support for professional certifications and technical skill development. Professional development allowance. Opportunities to work on challenging enterprise Data & AI initiatives. Exposure to modern cloud, data engineering, and AI technologies. Mentorship and opportunities for technical and career growth. Collaborative global environment focused on transparency, autonomy, and continuous improvement. Opportunities to contribute to technical communities and approved thought-leadership content.