66degrees

Architect

• Architect end-to-end, scalable, secure, and performant GenAI solutions using Gemini Enterprise. Design complex, multi-agent workflows, deciding between the no-code workbench and custom Agent Development Kit (ADK) systems for production tasks.
• Design the RAG-based data grounding architecture to securely connect Gemini Enterprise models to diverse, permission-aware enterprise data (e.g., BigQuery, Salesforce).
• Architect the security and governance framework, implementing data residency, access control, and agent monitoring via Gemini Enterprise's control planes.
• Serve as the lead technical advisor to C-level and IT leadership, defining the strategic value, ROI, and technical roadmap for Gemini Enterprise adoption.
• Facilitate client workshops (requirements, validation, UAT). Lead hands-on development of high-impact prototypes/MVPs to validate architecture and demonstrate business value.
• Create the technical integration strategy to embed Gemini across the client's technology stack (Google Workspace, core business applications).
• Produce high-quality architectural documents, design specs, and roadmaps for implementation teams.
• Stay current with industry trends and advanced AI/ML, including agentic frameworks.
• Act as a key resource and contributor, lending your expertise to adjacent projects, special initiatives, and strategic conversations that align with your core competencies.
• Collaborate with delivery, engineering, and sales to define scope, identify opportunities, and evolve the Gemini Enterprise offering.

Gemini Architect

Data Engineer

• Design, develop, and maintain scalable and efficient data pipelines using Google Cloud Platform (GCP) services.
• Implement and manage data transformation logic using Dataform (or dbt) to ensure data quality, consistency, and reusability.
• Lead and execute the migration of existing data solutions from SQL Server to GCP.
• Develop, test, and deploy data ingestion and processing scripts using Python.
• Manage and optimize data storage solutions in Google Cloud Storage (GCS).
• Monitor data pipeline performance, troubleshoot issues, and implement solutions for data integrity and reliability.
• Collaborate with data scientists, analysts, and other engineering teams to understand data requirements and deliver appropriate data solutions.

Data Engineer – Contract

Full-stack Engineer

• Design, develop, and deploy high-quality applications on GCP.
• Write clean, maintainable, and efficient Python code.
• Develop and maintain APIs and microservices.
• Implement best practices for cloud-native application development.
• Design and manage scalable cloud infrastructure using GCP services.
• Optimize performance and cost of cloud resources.
• Ensure the security and compliance of cloud infrastructure.
• Implement CI/CD pipelines using GCP tools and other industry-standard tools.
• Automate infrastructure provisioning, configuration management, and application deployment.
• Set up monitoring, logging, and alerting solutions to ensure application reliability and availability.
• Troubleshoot and resolve production issues.

Full Stack Engineer

Security Engineer

• Design and implement comprehensive AI security architecture, including governance frameworks, data protection controls, model security standards, and usage policies for enterprise AI systems
• Collaborate with the AI business deployment team to establish security requirements and controls for AI applications, ensuring alignment between business objectives and security standards
• Develop and enforce AI usage policies and security guardrails for employees, including guidelines for acceptable use of generative AI tools, prompt engineering security, and data sharing restrictions
• Establish security standards and best practices for AI/ML development teams, covering model training security, data pipeline protection, API security, and secure model deployment
• Conduct AI-specific threat modeling and risk assessments, identifying vulnerabilities such as prompt injection, data poisoning, model theft, adversarial attacks, and privacy leakage
• Define data classification and handling requirements for AI systems, ensuring sensitive customer information and personally identifiable information are appropriately protected in training datasets and model outputs
• Evaluate and recommend AI security tools and technologies, including data loss prevention for AI interactions, AI gateway solutions, model monitoring platforms, and security testing frameworks
• Partner with compliance and legal teams to ensure AI implementations meet regulatory requirements including insurance industry regulations, data privacy laws, and emerging AI-specific legislation
• Create security awareness training programs focused on AI risks, responsible AI usage, and secure development practices for different user personas across the organization
• Develop incident response procedures specific to AI security events, including model compromise, data leakage, and unauthorized AI tool usage
• Monitor the evolving AI security landscape and provide strategic guidance on emerging threats, vulnerabilities, and security best practices
• Establish metrics and reporting frameworks to measure AI security posture and communicate risk to executive leadership

AI Security Architect – Contract

• Design, implement, and manage robust, scalable, and cost-effective cloud-based data architectures on Google Cloud Platform (GCP), leveraging services like BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage, Cloud DataProc, Cloud Run, and Cloud Composer.
• Develop and maintain conceptual, logical, and physical data models to support various business needs.
• Design and implement solutions for processing large datasets using technologies such as Spark and Hadoop.
• Establish and enforce data governance policies, including data quality, security, compliance, and metadata management.
• Build and optimize data pipelines for efficient data ingestion, transformation, and loading.
• Monitor and tune data systems to ensure high performance and availability.
• Work closely with data engineers, data scientists, and other stakeholders to understand data requirements and provide architectural guidance.
• Stay current with the latest technologies and trends in data architecture and cloud computing.

Data Architect, GCP – Contract

Artificial Intelligence

• Dive deep into a wide range of data (tabular, text, image, etc.) to identify pain-points and deliver data-driven insights to our clients.
• Utilize analytical techniques to determine areas of opportunities to help meet business goals.
• Leverage GCP services to train and deploy off-the-shelf (Vertex AI/AutoML/BQML) or custom models to address a client’s business problem.
• Be a thought leader for your team on projects and contribute to key practice initiatives.
• Act as subject matter expert on pre-sales calls and requests for proposals.
• Drive successful delivery of analytics solutions.
• Create reports and presentations that showcase the value of your solution to our clients.
• Work with other members of the data science team to establish a center of excellence and create standard operating procedures, accelerators, and sales assets.
• Lead the design of technical solutions to meet the business needs of customers and clients.
• Provide technical leadership to customer and client engagements, including working with the sales team to develop and deliver technical presentations and proposals, and working with the delivery team to implement and support the technical solutions.
• Mentor and train junior team members and help them to develop their technical skills and knowledge.

AI/ML Architect

Sales

• Develop and execute a comprehensive regional sales strategy aligned with 66degrees' overall business objectives and channel partnership goals.
• Utilize market insights, sales data, and analytics to identify new growth opportunities, optimize sales processes, and forecast regional revenue accurately.
• Translate strategic objectives into actionable plans and measurable targets for the sales team.
• Recruit, onboard, and ramp high-performing team of sales professionals specializing in complex solutions.
• Provide expert coaching, mentorship, and constructive feedback to elevate individual and team performance, particularly in navigating multi-stakeholder deals and long sales cycles.
• Foster a positive, results-oriented, and resilient team culture that encourages continuous learning and adaptability.
• Empower team members to take ownership, innovate, and achieve their full potential.
• Maintain a deep understanding of 66degrees' comprehensive offerings, including AI/ML, Data & Analytics, Cloud Infrastructure, and Application Development services.
• Develop and continuously refine knowledge of the competitive landscape, industry trends, and the specific business challenges faced by clients in your region.
• Guide the team in positioning 66degrees' solutions to address complex customer pain points and deliver tangible business value.
• Oversee and ensure the successful execution of strategic, complex sales cycles, from prospecting and discovery to solution design, negotiation, and closing.
• Ensure the team maintains a customer-centric approach, focusing on understanding client needs, building long-term relationships, and exceeding expectations.
• Provide hands-on support and strategic guidance on key deals, helping the team navigate complex organizational structures and decision-making processes within large enterprises.
• Act as a pivotal liaison between the regional sales team and internal stakeholders, including solution architects, delivery teams, marketing, and executive leadership.
• Promote cross-functional collaboration to ensure seamless client experiences and effective solution delivery.
• Communicate clearly, concisely, and persuasively with team members, customers, and senior leadership.
• Leverage Salesforce and other sales enablement tools to manage the regional pipeline, track performance, and report on key metrics.
• Implement and optimize sales processes to improve efficiency, reduce friction in the sales cycle, and enhance overall productivity.

Director of Sales

Analytics Engineer

• Collaborate with stakeholders to understand business requirements and translate them into high-performing technical implementations.
• Work with Clients to enable them on the Power BI Platform, assisting them in building out an analytics ecosystem in Power BI from the ground up.
• Implement best practices for scalable, governed analytics, helping clients build out their analytics centers of excellence through hands-on technical execution.
• Utilize Power BI to design and develop interactive and visually appealing dashboards and reports for end-users.
• Write clean, efficient, and scalable code (DAX, M, Python as applicable) to support complex data transformations.
• Conduct performance tuning and optimization of data analytics solutions to ensure efficient processing and query performance at scale.
• Stay up to date with the latest trends and best practices in cloud data analytics, big data technologies, and data visualization tools.
• Collaborate with cross-functional teams to ensure seamless integration of data analytics solutions with existing systems and processes.
• Provide technical guidance and mentorship to junior team members, sharing knowledge and promoting engineering best practices.