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Lead design and implementation of Snowflake-based ingestion and ELT pipelines; build and optimize AWS data architectures (S3, Glue, Lambda, EMR); manage Airflow orchestration; implement data quality, validation, governance, and CI/CD practices; act as technical leader, mitigate risks, document processes, and engage with clients.

Lead design and implementation of Snowflake-based ingestion and ELT pipelines, orchestrate workflows with Airflow, ensure data quality and governance, optimize AWS data architectures (S3, Glue, Lambda, EMR), and provide technical leadership on client engagements.

The Senior Data Engineer will design and implement scalable data solutions, ensuring data quality and performance, and optimizing data pipelines while collaborating with cross-functional teams.

The Senior Data Engineer will design and implement scalable data solutions, focusing on data pipeline reliability, quality, and performance while collaborating with cross-functional teams.

Design, develop, and deploy AI/ML models and production systems. Collaborate with cross-functional teams, mentor engineers, and ensure model performance, scalability, and reliability. Drive technical strategy for AI solutions.

Senior Client Partner responsible for owning and growing a strategic TMT account (telecom/ISP). Lead account strategy, P&L, business development, proposals/SOWs, pricing negotiations, and client satisfaction. Connect client stakeholders to Blend360 capabilities, act as trusted advisor to senior executives, and drive expansion of analytics and AI engagements.

Define and implement deployment architecture for a containerized, microservice-style AI application on Azure Container Apps or Databricks Apps. Integrate deployments with existing enterprise CI/CD pipelines, configure environments, scaling, networking, secrets, monitoring, logging, alerting, RBAC, and operational controls. Collaborate with client IT, software engineering, AI engineering, and QA teams on production readiness, testing, release management, documentation, handover, and incident response.

Develop production software while enabling internal engineering teams through developer support, tooling, automation, architecture guidance, infrastructure as code, and security framework recommendations. The role uses .NET and C#, with Terraform and AWS exposure, and helps integrate AI knowledge into coding tools. Responsibilities include code reviews, testing, technical mentoring, documentation, workflow improvement, and resolving ambiguous development challenges.

Leads the technical direction, quality, and growth of an AI Engineering practice. Responsibilities include designing production AI architectures, overseeing major client engagements, setting engineering standards, leading technical workstreams, conducting design reviews, shaping proposals, advising executives, developing senior engineers, and defining hiring and capability plans. The role remains hands-on with architecture, code reviews, prototyping, and resolving complex technical issues across retrieval, agentic, evaluation, multilingual, scalability, cost, and reliability challenges.

Design, build, and deploy production-grade agentic AI systems that execute complex workflows using LLMs, orchestration frameworks, MCP tools, coding agents, APIs, and enterprise systems. Responsibilities include context and harness engineering, tool integration, RAG, agent evaluation, guardrails, reliability testing, cloud deployment, optimization, observability, and secure enterprise integration. The role requires translating business requirements into scalable AI applications with measurable impact beyond proof-of-concept implementations.