Engineering Manager to $8000

Salesforge is soon to become the number one platform of choice for sales organizations large and small. We have built a new category within the sales execution software space called programmatic sequencing where we match seller data (what is it that you sell) and buyer data across various sources to personalize every single email at any scale and in any language all powered by AI, led by a senior team of people that know what they're doing.

Imagine a Chief Revenue Officer responding back to an email saying "This is email greatness". That's exactly what we deliver at any scale and in any language. Now we're at a point where we're looking to hire more back-end and front-end developers into our small, but mighty team to keep crushing our revenue targets.

Now we are building autonomous AI agents that will book meetings with prospects on autopilot.

Culture?

We roll like a pack, our execution is godlike and we like good vibes along the way. No corporate BS or oldschool mentality. If this sounds exciting and you want to work on something that matters on a large scale, give us a shot.

Engineering Manager - Responsibilities

• Lead a small, high-velocity engineering team, owning execution, delivery predictability, and team health in a fast-moving startup environment.
• Run regular 1:1s, coaching engineers on growth, performance, and impact; create clear development plans and feedback loops.
• Keep engineers unblocked and productive by proactively removing execution bottlenecks and coordinating across functions.
• Partner with Product/PM to refine ideas into well-scoped technical tickets and milestones, enabling the team to plan and estimate without CTO dependency.
• Drive planning rituals (backlog grooming, sprint/kanban flow, retros), ensuring priorities are clear and work stays aligned with business goals.
• Guide technical design and architecture for backend services and APIs: review proposals, facilitate tradeoffs, and ensure scalability/reliability under growth.
• Help evolve distributed and message-driven systems when appropriate (e.g., SQS, RabbitMQ, Kafka), focusing on resilience and operability.
• Ensure data models and access patterns scale well across relational and document databases (e.g., PostgreSQL/MySQL, MongoDB).
• Uphold engineering excellence through strong code review culture, pragmatic documentation, and quality practices that reduce production risk.
• Foster a culture of ownership, clear communication, and continuous improvement across the team.