Role Description The Manager of Sales is responsible for driving annual sales for the Constellation Energy Solutions Asset Development and Management solutions in collaboration with technical sales manager, engineering and construction team in Constellation's commercial business. This position will be dedicated to the full lifecycle of sales from market analysis to customer prospecting to contract negotiation and execution of opportunities. The successful candidate will identify and unlock opportunities to increase the value and meet sales targets resulting in a differentiated experience and greater long-term value for Constellation. The sales manager will attract and retain top sales talent and coach the sales team to execute on assigned targets. The position will require extensive organization engagement. The key organization interfaces will include Constellation's Commodity Sales team, Products team, CTV, Association, Marketing, and other parts of Constellation where services may resonate with customers. Primary Duties and Accountabilities - Drive annual sales performance for Constellation Energy Solutions Asset Development & management to achieve sales targets. - Build and maintain a qualified sales pipeline in partnership with Retail sales teams. - Collaborate with internal stakeholders, to develop solutions and close customer contracts. - Partner with new and existing channel partners to grow CES Solutions opportunities. - Lead and develop sales team members to build a pipeline of qualified opportunities. - Ensure the CRM tool contains accurate sales pipeline data and reporting to support achievement of annual targets. Qualifications - Bachelor's degree - 8 years of experience leading teams across sales, asset development, demand response, demand side management, energy efficiency, retail sales, marketing, strategy consulting, or product management - Demonstrated experience in entrepreneurship, startup, or technology environments - Strong analytical, communication, and leadership skills - Strong presentation skills; capable of presenting externally and internally - Demonstrated ability to influence, build alignment, and drive adoption without direct authority - Demonstrated understanding of the company's commercial energy business units, personnel, and strategy - Strong written and verbal communication skills to support documentation, presentations, and stakeholder engagement - Ability to multi-task and work with teams and independently in a fast paced, dynamic environment, under deadline pressure with external and internal partners at all levels - Demonstrated self-starter with ability to plan and execute with minimal oversight; strong sense of ownership and commitment to excellence of all work products Preferred Qualifications - Experience developing structured energy transactions, including long-term Power Purchase Agreements and Energy Services Agreements with commercial & industrial, federal, and MUSH sectors Benefits - Competitive compensation - Bonus program - 401(k) with company match - Employee stock purchase program - Comprehensive medical, dental, and vision benefits - Robust wellbeing programs - Disability and life insurance benefits - Paid time off for vacation, holidays, and sick days

• Manage and grow engineering leads for Merchants Core and Merchants Growth • Run 1:1s, set goals, provide feedback, and develop your team • Own hiring for your teams — source, interview, and close strong engineers • Foster a culture of ownership, technical excellence, and direct communication • Own architectural decisions across billing, invoicing, checkout, dashboard, and the delivery promise engine • Write and review RFCs for non-trivial features — set the bar for how engineering decisions are made • Review AI-generated and human-written code with equal rigor — you understand every line that ships • Drive the evolution of Burq's merchant experience toward a full enterprise delivery platform • Own sprint health, backlog quality, and delivery predictability across both teams • Ensure KTLO (Keep the Lights On) work — billing reliability, notification infrastructure, account management — always has a home and never loses to feature pressure • Partner closely with the Merchants PM and designer to translate product strategy into engineering roadmaps • Maintain a clear boundary between Core (reliability, billing, KTLO) and Growth (product, promise engine, features) • Work directly with the Head of Engineering on org structure, hiring plans, and technical strategy • Collaborate with Customer Success on merchant operational pain — Core is the team closest to that surface • Partner with the Data team on financial reconciliation and analytics infrastructure

• Lead and grow a team of backend and platform engineers migrating post-op processing from a batch system to a real-time, event-driven architecture. • Partner with Product, Attack Engineering, and adjacent Platform teams to sequence the rework so customer value ships continuously rather than as one big-bang cutover. • Work with senior engineers on the team to shape the technical direction: event streaming, stream processing, storage, schema evolution, and replayable processing. • Invest in operational excellence — SLOs, observability, on-call, and incident response — as this system becomes central to every pentest Horizon3 runs. • Help translate existing batch-era logic (finding enrichment, attack path analysis, reporting) into streaming-friendly designs without regressing fidelity. • Recruit, mentor, and retain engineers who care about both distributed systems craft and the security domain. • Establish healthy team practices: design reviews, technical writing, clear API contracts with neighboring teams, and durable decision records.

Role Description Fetch is looking for a Senior Manager of Machine Learning Engineering to lead the team building and scaling machine learning capabilities across our Ad Platform. You will partner with Product, Data Science, Engineering, and business stakeholders to translate strategy into a measurable roadmap that improves advertiser outcomes, member experience, and marketplace performance. You will lead engineers through ambiguous, business-critical problems while maintaining a strong balance between product delivery, model quality, reliability, scalability, and long-term technical health. Role Responsibilities: - Lead and develop a team of machine learning engineers responsible for business-critical Ad Platform systems. - Translate product and technical strategy into quarterly and annual roadmaps with measurable product, technical, and delivery outcomes. - Guide the development of ML solutions for areas such as ad ranking, targeting, bidding, inventory forecasting, optimization, and measurement. - Partner with Product, Data Science, Analytics, and Engineering teams to define success metrics, experimentation strategies, and technical priorities. - Make sound trade-offs across delivery speed, model performance, scalability, reliability, maintainability, and technical debt. - Raise the engineering bar through strong design reviews, code reviews, operational ownership, and architectural standards. - Proactively identify technical and organizational risks before they constrain delivery or platform growth. - Coach engineers on system design, technical decision-making, execution, and career development. - Use data, experiments, incidents, system performance, and delivery metrics to guide priorities and improve team effectiveness. - Drive alignment and execution across teams with shared systems, goals, and dependencies. Qualifications - 8+ years of experience in software engineering, machine learning engineering, or a related technical field, including 2+ years managing and developing engineering teams. - Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience. - Experience managing and developing machine learning or software engineers in a product-focused environment. - Strong technical background building and operating production machine learning systems at scale. - Experience translating business and product objectives into technical roadmaps and measurable outcomes. - Strong understanding of the ML lifecycle, including data quality, feature development, training, evaluation, deployment, monitoring, and iteration. - Experience making technical trade-offs involving model quality, latency, scalability, reliability, and maintainability. - Ability to lead teams through medium-to-high ambiguity and complex cross-functional dependencies. - Demonstrated experience coaching senior engineers and raising technical and operational standards. - Strong communication and stakeholder-management skills, including the ability to influence without direct authority. - Proficiency with Python and SQL and experience with modern machine learning frameworks and cloud-based data or ML systems. - Experience establishing accountability for both delivery outcomes and the long-term technical health of owned systems. Preferred Requirements - Master’s degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, or a related technical field. - Experience building machine learning systems for advertising, recommendations, ranking, personalization, or marketplace optimization. - Familiarity with ad auction dynamics, bidding, targeting, inventory forecasting, attribution, and campaign measurement. - Experience leading teams responsible for low-latency, high-scale production systems. - Strong understanding of experimentation, causal inference, and incrementality measurement. - Experience with modern MLOps practices, feature platforms, model monitoring, and automated training and deployment pipelines. - Experience working with large-scale data processing and distributed systems. - Demonstrated success leading cross-team technical initiatives in a rapidly evolving product environment. Benefits - Competitive compensation packages including base, equity, and benefits.