Staff Engineer AI - Voice

Redefine the future of customer experiences. One conversation at a time.
At Nextiva, we’re reimagining how businesses connect, bringing together customer experience and team collaboration on a single, conversation centric platform. Powered by AI, driven by human innovation.
Our culture is forward thinking, customer obsessed and built on the belief that meaningful connections drive better business outcomes. Whether it’s through our signature Amazing Service®, the technology we create, or the experiences we cultivate, connection is at the core of who we are.
If you’re ready to collaborate with incredible people, make an impact, and help businesses everywhere deliver truly amazing experiences, this is where you belong.
Location: This is an onsite role based at Nextiva’s Bengaluru office (Wilshire III by MFAR, 492, Hobli, RHB Colony, Mahadevapura, Bengaluru, Karnataka 560048). Working together onsite strengthens how we operate, enabling faster decisions, clearer communication, and stronger execution, so you can make a greater impact and move work forward with speed and clarity.
In-Office Expectation: This role is expected to work onsite four days per week, with the potential to increase to five days per week, as required by the business. Specific scheduling and flexibility will be guided by your leader to support both team collaboration and individual productivity.
The Staff AI Engineer – Voice AI is a hands-on senior individual contributor role for an experienced engineer with deep expertise across AI/ML, LLM systems, software engineering, and distributed system design. This role will help architect, build, and scale Nextiva’s next generation of intelligent, real-time conversational and Agentic AI experiences.
As a Staff AI Engineer, you will operate at the intersection of AI engineering, real-time systems, system architecture, and hands-on software development. You will take ownership of complex AI capabilities from experimentation and early-stage technical solutioning through architecture, implementation, evaluation, production deployment, and continuous improvement.
This is not an architecture-only or research-only position. We are looking for someone who remains deeply hands-on, writes production-quality code, understands modern AI systems in depth, and can translate rapidly evolving AI technologies into reliable, scalable, low-latency production systems.
You will work across the complete Voice AI stack — including streaming audio, ASR, TTS, LLM reasoning and orchestration, tool/function calling, RAG and knowledge systems, agentic workflows, context and memory management, and real-time communications. You will help build AI agents capable of reasoning, maintaining context, interacting with enterprise systems, and executing complex multi-step workflows while delivering natural and reliable conversational experiences.
The role also carries significant technical leadership responsibility. You will drive architecture and design decisions, solve ambiguous technical problems, mentor engineers, influence engineering direction, and collaborate across Nextiva teams to advance the Voice AI platform.
We are seeking a Staff AI Engineer with 10+ years of engineering experience who combines deep AI/ML expertise with strong software engineering fundamentals and a track record of taking sophisticated AI capabilities from concept to production at scale.
Responsibilities
Architect, build, and scale real-time conversational and Agentic AI systems for Nextiva’s Voice AI platform.
Own complex AI engineering initiatives end to end, from experimentation and early-stage solutioning through architecture, implementation, evaluation, deployment, and production optimization.
Remain deeply hands-on with software development and contribute high-quality production code.
Design and build low-latency, highly available, scalable, and resilient distributed systems supporting real-time AI workloads.
Build and optimize Voice AI pipelines spanning streaming audio, ASR, TTS, LLM reasoning, tool/function calling, agent orchestration, and real-time communications.
Design AI agents capable of maintaining context, reasoning over information, interacting with enterprise systems, and executing complex multi-step workflows.
Develop and optimize LLM orchestration, RAG and knowledge systems, embeddings and retrieval, prompt/context engineering, agent state and memory, and workflow orchestration.
Evaluate and apply techniques including model fine-tuning, inference optimization, and transformer-based architectures where they improve product quality, latency, reliability, or cost.
Work with frameworks and technologies such as Pipecat, LiveKit, LangChain, LangGraph, n8n, and other LLM and agent orchestration technologies where appropriate.
Design APIs, asynchronous processing architectures, and event-driven systems that integrate AI capabilities with Nextiva products and enterprise systems.
Establish and evolve AI observability and evaluation frameworks, including tracing, offline and online evaluations, regression testing, conversational quality metrics, production monitoring, and systematic experimentation.
Develop guardrails and engineering mechanisms that improve AI quality, safety, reliability, and predictable production behavior.
Diagnose and optimize end-to-end conversational performance, including latency, model behavior, retrieval quality, agent execution, and overall conversational experience.
Drive architecture and technical design decisions for major Voice AI capabilities and help establish engineering patterns and standards for the platform.
Navigate ambiguous and rapidly evolving technical problems and translate them into practical, scalable engineering solutions.
Mentor engineers, provide technical guidance, and raise the engineering and AI capabilities of the broader team.
Collaborate across product, engineering, AI/ML, platform, and other Nextiva teams to deliver integrated Voice AI capabilities.
Stay current with advances in LLMs, Agentic AI, conversational AI, speech technologies, and AI engineering, and apply emerging approaches where they create meaningful product or engineering value.
Requirements
Basic Qualifications
10+ years of software engineering experience, with significant experience building complex production systems.
Deep hands-on expertise in AI/ML engineering, including experience building and deploying AI-powered applications in production.
Strong understanding of LLMs and modern generative AI systems, including LLM orchestration, prompt/context engineering, tool/function calling, and agentic workflows.
Experience designing and building Agentic AI systems, including agent state, memory, tool execution, workflow orchestration, and multi-step reasoning.
Experience with RAG and knowledge systems, including embeddings, retrieval strategies, vector search, context construction, and retrieval quality optimization.
Strong understanding of Machine Learning and Deep Learning fundamentals, including transformer architectures and modern model inference.
Experience with model evaluation, fine-tuning, and inference optimization.
Strong software engineering fundamentals and hands-on development experience in Python, Java, or Go, with strong Python experience preferred.
Strong system design and distributed systems capabilities.
Experience architecting scalable APIs, asynchronous processing systems, and event-driven architectures.
Experience taking AI or software capabilities from experimentation and design through production deployment and operation at scale.
Strong understanding of production engineering concerns including scalability, reliability, observability, performance, and fault tolerance.
Experience designing systems where low latency and real-time performance are critical.
Experience with AI evaluation and observability approaches such as tracing, offline/online evaluation, regression testing, production monitoring, and quality measurement.
Ability and willingness to remain deeply hands-on with coding and technical problem solving at Staff Engineer level.
Demonstrated ability to lead architecture and technical design discussions and influence engineering direction across teams.
Ability to operate effectively in ambiguous environments where product requirements, AI capabilities, and technical approaches are evolving.
Strong communication and collaboration skills across engineering, product, and technical stakeholders.
Preferred Qualifications
Experience building production Voice AI, conversational AI, or real-time AI systems.
Hands-on experience with ASR, TTS, streaming audio, speech processing, or real-time communication systems.
Experience with Pipecat, LiveKit, LangChain, LangGraph, n8n, or comparable AI/agent orchestration technologies.
Experience designing and operating LLM-powered agents in production.
Experience optimizing conversational AI systems for latency, reliability, conversational quality, and cost.
Experience with vector databases, embedding models, retrieval pipelines, and large-scale knowledge systems.
Experience with Docker and Kubernetes and deploying AI workloads in cloud-native environments.
Experience with production ML/AI infrastructure, model serving, inference platforms, and AI observability tooling.
Experience designing guardrails and evaluation systems for product

Work arrangement
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