Manager, Forward Deployed Engineering

About the role

As the Manager of Forward Deployed Engineering at Parloa, you will play a pivotal role in leading a specialized team responsible for deploying enterprise AI solutions. Your leadership will ensure that complex deployments are executed with precision, adhering to the highest standards of engineering quality. You will be at the forefront of managing technical projects that involve integrating AI systems into large-scale enterprise environments, working closely with clients and internal teams to deliver scalable, reliable, and efficient solutions. This role requires a strategic thinker with strong technical expertise and leadership skills, capable of navigating complex technical challenges and fostering a collaborative environment. Your efforts will directly impact the success of enterprise AI deployments, helping clients leverage cutting-edge technology to optimize their operations.

Key facts

What you'll do

• Lead and mentor a team of Forward Deployed Engineers, setting clear objectives, providing guidance, and conducting regular performance evaluations to foster professional growth.
• Manage staffing, resource allocation, and project planning across multiple strategic deployment initiatives, ensuring optimal utilization of team members and timely delivery.
• Oversee the entire engineering delivery lifecycle for deployments, including planning, execution, milestone tracking, and stakeholder communication, to ensure projects meet deadlines and quality standards.
• Develop and implement tracking and reporting systems to provide transparency into project progress, team capacity, and potential bottlenecks, enabling proactive management.
• Collaborate with clients and internal stakeholders to understand technical requirements, translating them into actionable deployment plans that align with business objectives.
• Provide hands-on technical guidance on architecture, integration, and implementation decisions, supporting the team in resolving critical production issues swiftly and effectively.
• Establish and promote scalable engineering practices by creating reusable frameworks, deployment standards, and automation tools to improve efficiency and consistency across projects.
• Incorporate insights and lessons learned from field deployments into product development cycles, working closely with core engineering teams to refine solutions and enhance future deployments.
• Build strong, long-term relationships with customer engineering teams and enterprise stakeholders, ensuring ongoing support, knowledge transfer, and successful outcomes.
• Maintain high standards of security, compliance, and quality assurance throughout all deployment activities, adhering to industry best practices and regulatory requirements.
• Coordinate with cross-functional teams, including product management, customer success, and sales, to align deployment strategies with overall business goals and customer needs.
• Stay informed about emerging technologies, industry trends, and best practices in enterprise AI, cloud computing, and deployment methodologies to continuously improve processes.
• Lead post-deployment reviews, gather feedback, and implement improvements to enhance future deployment efficiency and customer satisfaction.
• Act as a technical point of contact during deployments, providing expert support and ensuring that solutions are delivered according to specifications and standards.
• Support the development of documentation, training materials, and knowledge bases to facilitate smooth onboarding and ongoing support for deployed solutions.
• Promote a culture of continuous learning and innovation within the team, encouraging the adoption of new tools, techniques, and approaches to stay ahead in the field.

Requirements

• Minimum of 8 years of experience in software engineering, systems integration, DevOps, or data engineering, with significant responsibilities in production environments.
• Proven leadership experience managing and developing engineering teams, including responsibilities for hiring, coaching, performance management, and career development.
• Demonstrated success delivering complex technical projects within large enterprise settings, involving multiple stakeholders and cross-functional teams.
• Strong technical background in backend engineering, APIs, cloud services (preferably Azure), Kubernetes, infrastructure-as-code (Terraform), and databases such as MongoDB, MySQL, and Redis.
• Hands-on experience managing smaller technical projects from inception through to completion, troubleshooting issues, and implementing solutions in production environments.
• Excellent organizational skills with a focus on planning, prioritization, risk management, and delivering results without excessive process overhead.
• Strong communication skills, both written and verbal, capable of engaging confidently with customer engineering teams, senior stakeholders, and internal teams.
• Ability to translate complex technical concepts into clear, actionable plans and documentation.
• Experience working with AI/LLM-powered systems is preferred, especially in forward-deployed or solutions engineering contexts.
• Familiarity with industry standards for security, compliance, and data protection, including GDPR and ISO 27001.
• Ability to adapt to changing priorities and work effectively in a fast-paced environment.
• A proactive approach to problem-solving and continuous improvement, with a focus on delivering value to clients.

Nice to have

• Experience in developing or integrating AI/LLM-powered systems, particularly in enterprise or solutions engineering roles.
• Prior experience working in a client-facing or consulting capacity, managing technical deployments directly with customers.
• Knowledge of additional cloud platforms beyond Azure, such as AWS or Google Cloud, to bring broader cloud deployment expertise.
• Familiarity with container orchestration tools beyond Kubernetes, such as Docker Swarm or OpenShift.
• Understanding of enterprise security standards and best practices for deploying AI solutions at scale.
• Experience working within Agile or DevOps teams, promoting continuous integration and continuous deployment practices.

Skills & tools

Typescript, NodeJS, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Practical notes

Parloa is an e-verify employer in the USA. We are committed to maintaining the highest standards of data protection and compliance, including GDPR and ISO 27001. We offer equal opportunities to all qualified applicants, regardless of race, gender, sexual orientation, age, religion, national origin, disability status, or socioeconomic background. We value diversity and are dedicated to creating an inclusive environment where all team members can thrive. We support flexible working arrangements and are open to candidates based in Germany and the UK, working from our offices or remotely within these regions. Our hiring process involves multiple stages, including technical assessments and interviews, to ensure a good fit for both the candidate and the company. We encourage interested applicants to apply early and look forward to exploring how you can contribute to Parloa's mission of advancing enterprise AI solutions.