Join us on our mission to elevate customer experiences for people around the world. As a member of the Everise family, you will be part of a global experience company that believes in being people-first, celebrating diversity and incubating innovation. Our dedication to our purpose and people is being recognized by our employees and the industry. Our 4.6/5 rating on Glassdoor and our shiny, growing wall of Best Place to Work awards is a testament to our investment in our culture. Through the power of diversity, we celebrate all cultures for their uniqueness and strengths. With 13 centers around the world and a robust work at home program, we believe great things happen when we work with people who think differently from us. Find a job you’ll love today!
Summary:
The Head of Engineering (Vice President) for EverAI will play a pivotal role in leading the development of innovative AI-first contact center technology products and enterprise AI platforms. The role is focused on delivering cutting-edge solutions with speed, agility, scalability, and operational excellence. As the Head of Engineering, you will oversee all aspects of engineering, including AI platform engineering, full-stack development, infrastructure systems, databases, QA, and team management.
You will collaborate closely with Product Management, AI/ML teams, Solution Architects, Customer Success, and Sales teams to bring product visions to life and ensure our technology stack supports our strategic goals and customer commitments.
The role requires a highly hands-on engineering leader with strong exposure to modern GenAI/LLM ecosystems, enterprise-grade platform development, and customer-facing solutioning. The candidate should be comfortable operating in a hybrid environment where certain products/modules are developed in-house with proprietary IP, while other offerings leverage third-party platforms through strategic partnerships.
The individual will also actively contribute to technical pre-sales activities including customer demos, solution workshops, RFP/RFI responses, roadmap planning, annual operating plans and strategic technology initiatives for EverAI Labs.
Key Responsibilities:
Engineering Leadership:
Lead and manage a multidisciplinary engineering organization, including AI/ML engineers, full-stack developers, backend developers, platform engineers, DevOps, QA teams, architects, and engineering managers.
AI & Platform Engineering:
Drive architecture, development, and deployment of enterprise-grade AI applications, conversational AI systems, agentic workflows, knowledge assistants, analytics platforms, and automation products.
Technical Strategy:
Define and execute the technical strategy for scalable, secure, high-performance AI-native products and platforms aligned with business goals and product roadmap.
Hands-on Technical Oversight:
Provide deep technical guidance across:
- Python and Java ecosystems
- FastAPI and Spring Boot frameworks
- LLM orchestration frameworks such as LangChain, LlamaIndex, or Microsoft Semantic Kernel
- Retrieval-Augmented Generation (RAG) architectures
- Vector databases and semantic search systems
- Open-source and enterprise LLM ecosystems, including Llama and Qwen models
- API-first and microservices-based architectures
- Cloud-native deployments and distributed systems
AI/LLM Solution Architecture:
Guide teams in designing:
- Context management and memory frameworks
- Evaluation and observability pipelines for LLM systems
- Secure enterprise AI deployments
- Model serving, inference optimization, and scalable AI runtime architectures
Product Development & Delivery:
Oversee end-to-end product engineering lifecycle, ensuring timely delivery of high-quality releases with strong engineering rigor, observability, resiliency, and maintainability.
Strategic Partnerships & Third-Party Platforms:
Work closely with strategic technology partners and evaluate third-party AI platforms/products for integration, customization, white-labeling, and enterprise deployment.
Team Building:
Recruit, mentor, and retain top engineering talent while fostering a culture of innovation, accountability, ownership, and continuous learning.
Collaboration:
Partner closely with Product Management, Design, AI Research, Infrastructure, Security, Customer Success, and Go-To-Market teams to align engineering execution with business priorities.
Customer & Pre-Sales Engagement:
Support Sales and Customer Success teams in:
- Technical demos and solution walkthroughs
- Customer workshops and architecture discussions
- RFP/RFI/RFQ responses
- Enterprise solution positioning
- Technical due diligence and client evaluations
- Discussions with customer infrastructure, security, and enterprise architecture teams
Process Improvement:
Implement and optimize engineering processes, development standards, CI/CD pipelines, AI governance practices, and quality frameworks across the organization.
Innovation:
Stay abreast of advancements in Generative AI, Agentic AI, LLMOps, MLOps, multimodal AI, speech technologies, and enterprise AI ecosystems to continuously evolve EverAI’s capabilities.
Roadmap & Strategic Planning:
Contribute to technology roadmap creation, engineering planning, platform strategy, annual operating planning (AOP), and long-term innovation initiatives for EverAI Labs.
Budget & Risk Management:
Manage engineering budgets, vendor relationships, infrastructure costs, and technical risks while ensuring optimal utilization of resources and sustainable platform scalability.
Stakeholder Communication:
Provide regular updates to leadership on engineering execution, risks, roadmap progress, scalability considerations, and strategic opportunities.
Qualifications:
Experience:
- 12+ years of experience in software engineering and platform development
- Minimum 5+ years leading engineering teams in high-growth product organizations
- Strong experience building enterprise SaaS platforms, AI-native products, or large-scale distributed systems
- Experience working with both proprietary product development and third-party platform integrations/white-label ecosystems
Technical Expertise:
Strong hands-on expertise in:
- Programming Languages: Python, Java
- Frameworks: FastAPI, Spring Boot
- LLM Frameworks: LangChain, LlamaIndex or Microsoft Semantic Kernel
- LLM Ecosystems: Llama, Qwen, and other open-source/commercial LLMs
- RAG architectures and vector databases
- API-driven and microservices architectures
- Cloud platforms and containerized deployments
- Enterprise system integrations
- CI/CD, DevOps, observability, and security best practices
Good-to-have exposure:
- STT/TTS systems and speech AI ecosystems
- Voice AI and conversational AI platforms
- LLMOps/MLOps tooling
- GPU inference optimization and model deployment
Leadership Skills:
Demonstrated ability to lead and scale high-performing engineering organizations with strong execution discipline in fast-paced environments.
Problem Solving:
Strong analytical and architectural problem-solving skills with the ability to navigate ambiguity and make pragmatic technical decisions.
Collaboration:
Excellent cross-functional collaboration skills with the ability to align engineering execution with product, business, and customer priorities.
Communication Skills:
Strong executive communication and customer-facing presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
Education:
Bachelor’s degree in Computer Science, Engineering, or related field required. Master’s degree or equivalent experience preferred.
If you’ve got the skills to succeed and the motivation to make it happen, we look forward to hearing from you.
