Company Overview

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.

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If you’ve got the skills to succeed and the motivation to make it happen, we look forward to hearing from you.