ARC Careers

Day-in-the-Life: A CTO begins with a leadership team meeting to align technology strategy with business objectives, discussing how DSAI can drive innovation. They review progress on ARC-related projects, approve budgets for AI infrastructure, and meet with data science teams to evaluate model performance. Afternoons may involve presenting to the board or investors, mentoring engineering leads, or researching emerging tech trends. They ensure DSAI solutions scale and align with long-term goals.

Transferable Skills:

• Strategic Vision: Aligning technology with business strategy.

• Leadership: Managing tech teams and fostering innovation.

• Technical Expertise: Deep knowledge of DSAI, cloud, and systems architecture.

• Business Acumen: Translating technical capabilities into business value.

Career Progression:

• Entry-Level: Software Engineer or Data Scientist (technical foundation).

• Mid-Level: Software Architect or Director of Technology ($94,413–$184,959).

• Senior-Level: VP of Engineering ($200,000–$300,000).

• Executive-Level: CTO ($125,928–$400,000+).

Salary Range (2025, US):

• Entry-Level: $80,000–$125,000

• Mid-Level: $130,000–$200,000

• Senior-Level: $200,000–$300,000

• Executive-Level: $250,000–$400,000+

Day-in-the-Life: A Solutions Architect starts the day reviewing project requirements and meeting with stakeholders (e.g., clients, product managers) to understand business needs. They design DSAI-driven system architectures, selecting appropriate cloud platforms, AI models, or data pipelines. They might collaborate with data scientists to integrate machine learning models into scalable solutions, create technical diagrams, and present proposals to clients. Afternoons involve troubleshooting implementation issues, coordinating with development teams, and ensuring alignment with business goals. They may also research emerging technologies to optimize designs.

Transferable Skills:

• Technical Design: Expertise in system architecture, cloud platforms (e.g., AWS, Azure), and DSAI integration.

• Problem-Solving: Translating complex business problems into technical solutions.

• Communication: Explaining technical concepts to non-technical stakeholders.

• Project Management: Coordinating cross-functional teams and managing timelines.

Career Progression:

• Entry-Level: Junior Solutions Architect or Systems Analyst (focus on specific components).

• Mid-Level: Solutions Architect or Lead Solutions Architect (designing end-to-end systems).

• Senior-Level: Principal Architect or Director of Solutions Architecture (overseeing multiple projects, strategic planning).

• Executive-Level: CTO or VP of Technology (aligning tech strategy with business goals).

Salary Range (2025, US):

• Junior: $80,000–$120,000

• Mid-Level: $130,000–$200,000

• Senior/Principal: $180,000–$250,000

• Executive (CTO): $200,000–$400,000+

Day-in-the-Life: An Enterprise Architect designs the overarching IT strategy, ensuring DSAI solutions integrate with enterprise systems. They start by reviewing business objectives and mapping them to technical capabilities. They collaborate with Solutions Architects and data scientists to ensure AI scalability and compliance. Afternoons involve presenting strategies to executives, assessing tech stacks, or researching AI governance frameworks.

Transferable Skills:

• Strategic Planning: Aligning IT with business goals.

• Systems Integration: Ensuring DSAI compatibility with enterprise systems.

• Governance: Managing compliance and security.

• Leadership: Guiding cross-functional teams.

Career Progression:

• Entry-Level: Systems Analyst ($60,000–$90,000).

• Mid-Level: Enterprise Architect ($120,000–$180,000).

• Senior-Level: Senior Enterprise Architect ($180,000–$250,000).

• Executive-Level: Chief Architect or CTO ($250,000–$400,000+).

Salary Range (2025, US):

• Entry-Level: $60,000–$100,000

• Mid-Level: $120,000–$200,000

• Senior-Level: $200,000–$280,000

• Executive-Level: $280,000–$450,000+

Day-in-the-Life: A Technical Consultant meets with clients to assess their technical challenges, often related to DSAI implementation (e.g., deploying a predictive analytics system). They analyze existing systems, propose DSAI-driven solutions, and create detailed implementation plans. They may code prototypes, train client staff, or troubleshoot integration issues. Afternoons involve documenting findings, preparing client presentations, or collaborating with data engineers to ensure solution feasibility.

Transferable Skills:

• Technical Expertise: Knowledge of DSAI tools, cloud platforms, and system integration.

• Client Management: Building trust and managing expectations.

• Analytical Thinking: Diagnosing technical issues and designing solutions.

• Communication: Simplifying complex technical details for clients.

Career Progression:

• Entry-Level: Junior Technical Consultant ($67,000–$80,000).

• Mid-Level: Technical Consultant ($81,316–$118,000).

• Senior-Level: Senior Technical Consultant or IT Project Manager ($100,000–$150,000).

• Executive-Level: Partner or Director of Consulting ($150,000–$250,000+).

Salary Range (2025, US):

• Entry-Level: $67,000–$80,000

• Mid-Level: $81,000–$120,000

• Senior-Level: $120,000–$180,000

• Executive-Level: $180,000–$300,000+

Day-in-the-Life: A Management Consultant focusing on DSAI projects starts by analyzing a client’s business processes, identifying opportunities for AI-driven efficiency (e.g., optimizing supply chains with predictive models). They conduct stakeholder interviews, gather data, and develop strategic recommendations. Afternoons involve presenting findings to clients, facilitating workshops, or collaborating with technical teams to ensure feasibility. They may also research industry trends to inform solutions.

Transferable Skills:

• Strategic Thinking: Aligning DSAI solutions with business goals.

• Data Analysis: Interpreting data to drive recommendations.

• Presentation Skills: Delivering compelling proposals to executives.

• Collaboration: Working with diverse teams to implement solutions.

Career Progression:

• Entry-Level: Analyst or Junior Consultant ($60,000–$90,000).

• Mid-Level: Consultant ($90,000–$130,000).

• Senior-Level: Senior Consultant or Manager ($130,000–$200,000).

• Executive-Level: Partner or Director ($200,000–$400,000+).

Salary Range (2025, US):

• Entry-Level: $60,000–$90,000

• Mid-Level: $90,000–$140,000

• Senior-Level: $140,000–$220,000

• Executive-Level: $220,000–$500,000+

Day-in-the-Life: A Data Scientist starts by analyzing datasets to develop or refine AI models for ARC projects (e.g., predictive maintenance systems). They write code in Python or R, experiment with algorithms, and validate model performance. They meet with Solutions Architects to integrate models into broader systems and present insights to stakeholders. Afternoons involve debugging code, documenting findings, or researching new DSAI techniques.

Transferable Skills:

• Machine Learning: Building and deploying AI models.

• Data Analysis: Extracting insights from complex datasets.

• Coding: Proficiency in Python, R, or SQL.

• Collaboration: Working with technical and business teams.

Career Progression:

• Entry-Level: Junior Data Scientist ($80,000–$110,000).

• Mid-Level: Data Scientist ($110,000–$150,000).

• Senior-Level: Senior Data Scientist or Data Science Manager ($150,000–$200,000).

• Executive-Level: Chief Data Officer ($200,000–$350,000+).

Salary Range (2025, US):

• Entry-Level: $80,000–$120,000

• Mid-Level: $120,000–$160,000

• Senior-Level: $160,000–$220,000

• Executive-Level: $220,000–$400,000+

Day-in-the-Life: A Machine Learning Engineer codes and optimizes AI models for ARC projects, such as anomaly detection systems. They start by refining algorithms, training models on cloud platforms, and monitoring performance metrics. They collaborate with Solutions Architects to deploy models in production and troubleshoot issues. Afternoons may involve researching new ML frameworks or mentoring junior engineers.

Transferable Skills:

• ML Development: Building scalable AI models.

• Cloud Computing: Deploying models on AWS, Azure, etc.

• Problem-Solving: Optimizing algorithms for performance.

• Teamwork: Collaborating with data scientists and architects.

Career Progression:

• Entry-Level: Junior ML Engineer ($80,000–$120,000).

• Mid-Level: Machine Learning Engineer ($120,000–$180,000).

• Senior-Level: Senior ML Engineer ($180,000–$250,000).

• Executive-Level: Director of AI/ML or CTO ($250,000–$400,000+).

Salary Range (2025, US):

• Entry-Level: $80,000–$120,000

• Mid-Level: $120,000–$200,000

• Senior-Level: $200,000–$280,000

• Executive-Level: $280,000–$450,000+

Day-in-the-Life: A CPO begins by reviewing product performance metrics, focusing on DSAI-driven features (e.g., recommendation engines). They meet with product managers to refine the product roadmap, ensuring AI features align with customer needs. They collaborate with CTOs and data scientists to prioritize development tasks and may present product strategies to the CEO or board. Afternoons involve customer feedback sessions or mentoring product teams.

Transferable Skills:

• Product Strategy: Defining DSAI-driven product visions.

• Customer Focus: Translating user needs into product features.

• Leadership: Guiding cross-functional teams.

• Data-Driven Decision Making: Using analytics to inform strategy.

Career Progression:

• Entry-Level: Product Manager ($80,000–$120,000).

• Mid-Level: Senior Product Manager or Director of Product ($120,000–$180,000).

• Senior-Level: VP of Product ($180,000–$250,000).

• Executive-Level: CPO ($200,000–$400,000+).

Salary Range (2025, US):

• Entry-Level: $80,000–$120,000

• Mid-Level: $120,000–$200,000

• Senior-Level: $200,000–$300,000

• Executive-Level: $250,000–$400,000+

Day-in-the-Life: An AI Product Manager reviews customer feedback on DSAI features and prioritizes product backlog tasks. They collaborate with data scientists to define AI model requirements and work with engineers to ensure seamless integration. They may run A/B tests to evaluate feature performance and present results to leadership. Afternoons involve stakeholder meetings or researching market trends to inform product strategy.

Transferable Skills:

• Product Management: Defining and prioritizing DSAI features.

• Technical Knowledge: Understanding AI/ML workflows.

• Stakeholder Engagement: Aligning teams and customers.

• Agile Methodologies: Managing development sprints.

Career Progression:

• Entry-Level: Associate Product Manager ($70,000–$100,000).

• Mid-Level: AI Product Manager ($100,000–$150,000).

• Senior-Level: Senior Product Manager ($150,000–$200,000).

• Executive-Level: VP of Product or CPO ($200,000–$400,000+).

Salary Range (2025, US):

• Entry-Level: $70,000–$110,000

• Mid-Level: $110,000–$160,000

• Senior-Level: $160,000–$220,000

• Executive-Level: $220,000–$400,000+

Day-in-the-Life: An IT Project Manager oversees ARC project timelines, ensuring DSAI components are delivered on schedule. They start with a team stand-up to track progress, resolve blockers, and allocate resources. They coordinate with Solutions Architects and data scientists to align technical deliverables with project goals. Afternoons involve risk assessments, stakeholder updates, and budget reviews.

Transferable Skills:

• Project Management: Managing timelines, budgets, and teams.

• Risk Management: Identifying and mitigating project risks.

• Communication: Liaising between technical and business teams.

• Agile/Scrum: Leading development sprints.

Career Progression:

• Entry-Level: Junior Project Manager ($60,000–$90,000).

• Mid-Level: IT Project Manager ($90,000–$130,000).

• Senior-Level: Senior Project Manager ($130,000–$180,000).

• Executive-Level: Program Director or VP of Operations ($180,000–$300,000+).

Salary Range (2025, US):

• Entry-Level: $60,000–$90,000

• Mid-Level: $90,000–$140,000

• Senior-Level: $140,000–$200,000

• Executive-Level: $200,000–$350,000+