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Staff AI Software Engineer

Nextiva

Bengaluru

8-12 years

Today

$60.2K–81.9K/yr

Full time

Onsite

Skills Required

LLM

Gen AI

Agentic AI

Retrieval Architectures

GCP

AWS

Java

Python

Go

MLOps

DevOps

CI/CD

Infrastructure as Code

Observability

Reliability

Description

Nextiva is hiring a Staff AI Engineer to build an internal AI platform that improves engineering and business workflows. The role sits at the intersection of software engineering, system architecture, AI engineering, cloud infrastructure, and developer productivity.

Company: Nextiva

Role: Staff AI Engineer

Location: Bengaluru office (onsite, 4 days per week with potential to increase to 5 days per week)

Experience

- Significant professional software engineering experience building and operating complex, production-scale systems
- Hands-on experience designing and building AI/ML or generative AI solutions that have reached production and/or delivered measurable business outcomes
- Robust software architecture and system design skills for distributed or large-scale systems
- Programming and software engineering fundamentals in one or more production languages such as Java, Python, Go, or equivalent
- Hands-on experience with LLMs, generative AI, AI agents, or AI-enabled application architectures
- Experience taking AI solutions beyond prototypes into deployment, operationalization, monitoring, security, reliability, and scale
- Deep hands-on experience with GCP and/or AWS designing and operating cloud-native production systems
- Strong understanding of DevOps, CI/CD, infrastructure as code, observability, reliability, and production operations
- Strong understanding of application, infrastructure, data, and AI security considerations
- Strong understanding of the end-to-end software development lifecycle, developer workflows, and large software systems and codebases
- Ability to evaluate technical trade-offs based on problem, business outcome, operational requirements, and long-term maintainability
- Strong technical judgment in ambiguous, cross-functional problem spaces
- Ability to influence technical direction across teams without relying solely on organizational authority

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 adopt AI-powered automation safely and efficiently
- 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 software engineering principles to AI systems including modular architecture, testing, reliability, performance, maintainability, and fault tolerance




- Design and implement 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
- Work deeply within GCP and/or AWS to design cloud-native architectures and infrastructure for secure, reliable, scalable production workloads
- Partner with infrastructure, DevOps, security, architecture, and engineering teams to establish production standards and operational guardrails
- Understand complex software systems and large codebases to identify opportunities where AI can improve developer workflows
- Evaluate emerging AI models, frameworks, agent architectures, and developer technologies for meaningful value
- Establish reusable engineering patterns and technical standards that accelerate AI adoption without compromising security, reliability, or maintainability
- 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
- Measure the impact of delivered solutions and continuously optimize them using production data, user feedback, and business results
- Identify high-value opportunities across the technology platform and organization to improve engineering and business processes

Additional Responsibilities

- Build and operationalize agentic SDLC capabilities that improve how engineers design, build, test, review, deploy, operate, and maintain software
- Deliver measurable improvements in engineering effectiveness, productivity, quality, velocity, cost, or customer outcomes
- Develop reusable architecture, services, infrastructure, patterns, and guardrails for the internal AI platform
- Establish clear success metrics for automation opportunities and demonstrate tangible business impact
- Operate across the breadth of the technology platform and organization rather than a single product or domain

Nice To Have

- Experience designing or implementing agentic AI systems, multi-step AI workflows, tool-using agents, or autonomous or semi-autonomous engineering workflows
- Experience applying AI to developer productivity, software engineering, code generation, testing, code review, incident management, or other SDLC stages
- Experience building internal developer platforms, engineering productivity platforms, or enterprise automation capabilities
- Experience with AI evaluation frameworks, model or agent observability,



prompt and context management, retrieval architectures, and production AI quality measurement
- Experience working across traditional software engineering and AI engineering
- Experience driving technical initiatives that span multiple teams, systems, or organizational domains
- Experience operating in high-growth SaaS or similarly complex technology environments

More Skills Software engineering, System architecture, AI engineering, Cloud infrastructure, Developer productivity, Agentic workflows, SDLC, AI/ML, AI-enabled application architectures, Production operations, Security, APIs, Data sources, Internal platforms, Enterprise systems, Containers, Kubernetes, Cloud-native services, Distributed systems, Event-driven architectures, Identity and access management, Secrets management, Model APIs, Evaluation tooling, Prompt management, Context management

Other

- Nextiva focuses on customer experience and team collaboration through an AI-powered, conversation-centric platform
- Work is expected onsite four days per week, with possible increase to five days per week based on business needs
- Nextiva values a customer-obsessed, forward-thinking culture centered on meaningful connections
- Core competencies highlighted are Drives Results, Critical Thinker, and Right Attitude
- Total rewards include medical insurance for employee, spouse, up to two dependent children, and parents or in-laws
- Group Term and Group Personal Accident Insurance are provided for the employee only
- Work-life balance benefits include privilege leave, paid sick leave, casual leave, maternity leave, paternity leave, birthday off, and paid holidays
- Financial security benefits include Provident Fund and Gratuity
- Wellness offerings include an Employee Assistance Program and comprehensive wellness initiatives
- Growth includes ongoing learning and development opportunities and career advancement
- Nextiva states it does not charge fees or require deposits during hiring
- Verification note: genuine communications come from official Nextiva email addresses ending in @
- Founded in 2008; headquartered in Scottsdale, Arizona; global teams; trusted by over 100,000 businesses and 1M+ users worldwide

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