Presales Engineer - Date & AI Engineering

Computer Task Group, Inc•UNAVAILABLE, UNAVAILABLE

5d•Remote

About The Position

CTG is seeking an experienced Presales Solution Engineer to join our Data & AI practice. This individual will act as the technical bridge between our sales organization and clients, translating complex business problems into compelling, technically sound solution architectures spanning modern data platforms and AI/ML capabilities. You will be a trusted technical advisor throughout the sales cycle, from discovery and requirements gathering through solution design, demonstration, proof-of-concept (POC), and handoff to delivery teams. The ideal candidate combines deep technical fluency in data platforms (e.g., Microsoft Fabric, Databricks, Snowflake) and AI engines/frameworks with strong client-facing consulting skills, and has a track record of influencing enterprise deals through credible, well-articulated technical solutions.

Requirements

10–15 years of overall experience in data, analytics, or AI-related technical roles.
Minimum 5 years specifically in a Presales / Solutions Engineering / Solutions Architecture capacity, ideally within a consulting, systems integrator, or technology vendor environment.
Demonstrated success supporting enterprise sales cycles and influencing deal outcomes through technical credibility.
Experience responding to RFPs/RFIs and leading technical proposal development.
Strong hands-on knowledge of modern data platforms, including one or more of: Microsoft Fabric / Azure Synapse / Azure Data Factory, Databricks (Lakehouse architecture, Delta Lake, Unity Catalog), Snowflake, AWS (Redshift, Glue, SageMaker) or Google Cloud (BigQuery, Vertex AI)
Working knowledge of AI/ML engines and frameworks, including: Generative AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic/OpenAI APIs), Traditional ML/MLOps tooling (MLflow, Kubeflow, Azure ML, SageMaker), LLM application patterns (RAG, agentic workflows, vector databases)
Solid understanding of data architecture concepts: data lakes/lakehouses, data warehousing, ETL/ELT pipelines, data governance, data quality, and master data management.
Familiarity with data security, privacy, and compliance frameworks (GDPR, HIPAA, SOC 2, etc.) as they apply to data and AI solutions.
Ability to read and discuss architecture diagrams, and where needed, build basic proof-of-concept configurations (SQL, Python/PySpark, notebooks).
Excellent client-facing communication skills able to present to both technical architects and C-level executives.
Strong discovery and requirements-gathering skills; able to ask the right questions to uncover true business needs.
Confident whiteboarding and storytelling ability to translate technical concepts into business value.
Strong stakeholder management, negotiation, and objection-handling skills.
Self-starter who can manage multiple concurrent opportunities and shifting priorities.
Collaborative team player who works effectively with sales, delivery, product, and partner teams.
Flexibility to learn new technologies and methodologies and stay ahead of market trends in terms of technology
Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's a plus) or equivalent by experience.

Nice To Haves

Prior experience at a systems integrator, consulting firm, or hyperscaler (Microsoft, AWS, Google, Databricks, Snowflake) in a presales or solutions capacity.
Vertical industry expertise (e.g., manufacturing, technology, healthcare, energy) relevant to CTG's client base.
Experience building or supporting Center of Excellence (CoE) initiatives for Data & AI.
Familiarity with agentic AI frameworks, copilots, or enterprise AI adoption strategies.
Public speaking, webinar, or thought-leadership experience (blogs, conference talks) in the Data & AI space.
Relevant certifications preferred, such as: Microsoft Certified: Fabric Analytics Engineer / Azure Data Engineer / Azure AI Engineer, Databricks Certified Data Engineer / Solutions Architect, AWS/GCP data or ML certifications, Snowflake SnowPro certification.

Responsibilities

Partner with Account Executives and Sales leadership to qualify opportunities and shape win strategies for Data & AI engagements.
Lead technical discovery sessions with client stakeholders (business and IT) to understand current-state data architecture, pain points, and desired business outcomes.
Translate business requirements into technical solution designs, reference architectures, and value propositions tailored to the client's environment.
Serve as the primary technical point of contact during the sales cycle, building trust and credibility with client architects, data leaders, and executives.
Design end-to-end data and AI solution architectures leveraging platforms such as Microsoft Fabric, Databricks, Snowflake, Azure Synapse, AWS Redshift/SageMaker, or Google BigQuery/Vertex AI.
Develop solution blueprints covering data ingestion, data engineering, data governance, analytics/BI, MLOps, and AI application layers.
Ensure proposed architectures address scalability, security, compliance, cost optimization, and integration with existing client ecosystems.
Build and deliver tailored product demonstrations, technical presentations, and workshops that showcase platform capabilities aligned to client needs.
Design, scope, and execute proof-of-concept (POC) and proof-of-value (POV) engagements, working cross-functionally with delivery, engineering, and partner teams.
Develop responses to RFPs/RFIs, including technical narratives, architecture diagrams, and effort estimates.
Create and maintain reusable presales assets: demo environments, solution accelerators, architecture templates, and battlecards.
Stay current on the evolving Data & AI landscape, including platform updates, competitive positioning, and emerging AI capabilities.
Provide technical input on pricing, licensing, and deployment models (SaaS, hybrid, on-prem) in partnership with sales and vendor partners.
Act as a liaison with technology partners (Microsoft, Databricks, Snowflake, AWS, Google Cloud) for co-selling motions, technical enablement, and joint solutioning.
Mentor junior presales/solutions engineers and contribute to building presales best practices and methodology.
Support smooth transition of won opportunities to delivery/implementation teams with clear documentation of scope, architecture, and client expectations.