Staff AI Engineer (Agentic AI)

OpenKrill; United States; Remote; USD 160,000 - 230,000; Full time

Job summary

Nextiva is seeking a Staff AI Engineer to build an internal AI platform shaping how we work across engineering and the organization. This hands-on role sits at the intersection of backend/platform engineering, AI, and cloud infrastructure.

You will design and deliver production-grade agentic workflows across the SDLC, drive observability and security, and provide technical leadership across teams to turn AI capabilities into measurable business value.

Qualifications

• 10+ years of professional software engineering experience.
• Hands-on AI/ML solutions in production with measurable impact.
• Strong architecture and design for distributed systems.
• Proficiency in Java, Python, or Go.
• Experience with AI agents and agentic workflows.
• Deep GCP/AWS expertise and cloud-native design.
• DevOps, CI/CD, and observability focus.
• Security-conscious in system design.

Responsibilities

• Architect and deliver production-grade AI systems and agentic workflows.
• Design scalable internal platform capabilities for AI automation.
• Lead end-to-end implementation from problem definition to deployment.
• Build integrations between AI models, tools, and engineering workflows.
• Apply robust software engineering principles to AI systems.
• Establish observability, security, and reliability patterns.
• Provide Staff-level technical leadership and mentorship.
• Translate business problems into executable technical strategies.

Skills

AI/ML in production

Cloud (GCP/AWS)

Backend architecture

Software design

CI/CD & DevOps

Observability & security

Java/Python/Go

Tools

GCP

AWS

Job description

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: While this role is open to remote candidates across India, team members located near our Bengaluru office (Wilshire III by MFAR, 492, Hobli, RHB Colony, Mahadevapura, Bengaluru, Karnataka 560048) are expected to work onsite four days per week, with the potential to increase to five days per week to support collaboration, speed, and execution.

Nextiva is looking for a Staff AI Engineer to help build an internal AI platform that will shape how we work across engineering and the broader organization.

This is a Staff-level, hands-on individual contributor role at the intersection of backend/platform engineering, system architecture, AI, cloud infrastructure, and developer productivity. You’ll design and build production-grade agentic workflows across the software development lifecycle (SDLC) and intelligent automation that improves engineering and business processes across Nextiva.

Working across Nextiva’s technology platform, you’ll identify high-value opportunities, architect solutions, and take them from concept through deployment, operationalization, security, observability, and scale. You’ll also provide technical leadership and influence across engineering teams.

We are looking for an engineer who understands that AI is a means to a business outcome—not the outcome itself and can turn promising capabilities into reliable systems that create measurable value.

Top 3 Outcomes (first 12 months)

• - Build and operationalize agentic SDLC capabilities: Architect and deliver production-grade AI workflows that materially improve how Nextiva engineers design, build, test, review, deploy, operate, and maintain software, with measurable improvements in engineering effectiveness.
• - Establish a scalable internal AI platform: Develop reusable architecture, services, infrastructure, patterns, and guardrails that enable AI-powered workflows to move reliably from experimentation into secure, observable, production-scale operation.
• - Deliver measurable business impact through AI and automation: Identify and execute high-value automation opportunities across engineering and business processes, establishing clear success metrics and demonstrating tangible improvements in productivity, quality, velocity, cost, or customer outcomes.

Key Responsibilities

• - Architect, build, deploy, and operate production-grade AI systems and agentic workflows across the SDLC and broader business processes.
• - Design scalable internal platform capabilities that enable teams across Nextiva to safely and efficiently adopt AI-powered automation.
• - Own solutions end-to-end—from problem definition and architecture through implementation, deployment, observability, security, scaling, and ongoing operation.
• - Build robust integrations between AI models, agents, developer tooling, internal platforms, enterprise systems, APIs, data sources, and engineering workflows.
• - Apply strong software engineering principles to AI systems, including modular architecture, testing, reliability, performance, maintainability, and fault tolerance.
• - Design approaches for AI evaluation, observability, quality measurement, failure handling, and continuous improvement in production.
• - Make pragmatic architectural and technology decisions based on business outcomes, engineering constraints, risk, and total cost of ownership rather than technology trends.
• - Work deeply within GCP and/or AWS, designing cloud-native architectures and infrastructure capable of supporting secure, reliable, scalable production workloads.
• - Partner with infrastructure, DevOps, security, architecture, and engineering teams to establish reusable engineering patterns, technical standards, and operational guardrails for AI-powered systems.
• - Understand complex software systems and large codebases to identify opportunities where AI can improve developer workflows across the end-to-end SDLC.
• - Evaluate emerging AI models, frameworks, agent architectures, and developer technologies to determine where they can create meaningful value for Nextiva.
• - Provide Staff-level technical leadership through architecture reviews, design decisions, technical mentorship, and influence across engineering teams.
• - Translate ambiguous business and engineering problems into clear technical strategies and executable solutions, measuring and optimizing impact based on production data, user feedback, and business results.

Requirements

Must-have

• - 10+ years of professional software engineering experience, with demonstrated experience designing, building, and operating complex production-scale systems.
• - Demonstrable hands-on experience designing and building AI/ML or generative AI solutions that have reached production and/or delivered measurable business outcomes.
• - Strong software architecture and system design skills, including experience making consequential technical decisions for distributed or large-scale systems.
• - Strong programming and software engineering fundamentals in one or more production languages such as Java, Python, Go, or equivalent.
• - Hands-on experience working with LLMs, generative AI, AI agents, or AI-enabled application architectures, beyond simply consuming AI productivity tools.
• - Experience taking AI solutions beyond prototypes into deployment, operationalization, monitoring, security, reliability, and scale.
• - Deep hands-on experience with GCP and/or AWS, including designing and operating cloud-native production systems—not solely familiarity with cloud services or consoles.
• - Strong understanding of DevOps, CI/CD, infrastructure as code, observability, reliability, and production operations.
• - Strong understanding of application, infrastructure, data, and AI security considerations and the ability to incorporate appropriate controls into system architecture.
• - Strong understanding of the end-to-end software development lifecycle, developer workflows, and the challenges of working within large software systems and codebases.
• - Ability to evaluate technical trade-offs and select technologies based on the problem, desired business outcome, operational requirements, and long-term maintainability.
• - Strong technical judgment and the ability to operate effectively in ambiguous, cross-functional problem spaces.
• - Ability to influence technical direction across teams without relying solely on organizational authority.

Preferred

• - Experience designing or implementing agentic AI systems, multi-step AI workflows, tool-using agents, or autonomous/semi-autonomous engineering workflows.
• - Experience applying AI to developer productivity, software engineering, code generation, testing, code review, incident management, or other stages of the SDLC.
• - Experience building internal developer platforms, engineering productivity platforms, or enterprise automation capabilities.
• - Experience with AI evaluation frameworks, model/agent observability, prompt and context management, retrieval architectures, and production AI quality measurement.
• - Experience spanning traditional software engineering and AI engineering—for example, a strong backend, platform, or distributed‑systems engineering foundation combined with substantial hands‑on AI engineering experience.
• - Experience driving technical init