3 hours ago
Remote, IndiaStaff+
Responsibilities
- Architect, build, deploy, and operate production-grade AI systems and agentic workflows across the SDLC and business processes.
- Design reusable internal AI platform capabilities, infrastructure, patterns, and guardrails for secure and reliable AI adoption.
- Own solutions from problem definition and architecture through implementation, deployment, observability, security, scaling, and ongoing operation.
- Integrate AI models and agents with developer tooling, internal platforms, enterprise systems, APIs, data sources, and engineering workflows.
- Design AI evaluation, observability, quality measurement, failure handling, and continuous-improvement approaches for production systems.
- Make architecture and technology decisions based on business outcomes, engineering constraints, risk, and total cost of ownership.
- Design and operate secure, reliable, scalable cloud-native workloads in GCP and/or AWS.
- Partner with infrastructure, DevOps, security, architecture, and engineering teams on technical standards and operational guardrails.
- Identify opportunities to improve developer workflows across the end-to-end SDLC using AI and automation.
- Provide staff-level technical leadership through architecture reviews, design decisions, mentorship, and cross-team influence.
- Measure and optimize the impact of AI solutions using production data, user feedback, and business results.
Requirements
- 10+ years of professional software engineering experience designing, building, and operating complex production-scale systems.
- Hands-on experience designing and building AI/ML or generative AI solutions that reached production or delivered measurable business outcomes.
- Strong software architecture and system design skills for distributed or large-scale systems.
- Strong programming 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 beyond using AI productivity tools.
- Experience taking AI solutions from prototypes through deployment, operationalization, monitoring, security, reliability, and scale.
- Deep hands-on experience designing and operating cloud-native production systems with GCP and/or AWS.
- 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 software development lifecycle, developer workflows, and large software systems and codebases.
- Ability to evaluate technical trade-offs, make pragmatic technology choices, and work effectively in ambiguous cross-functional environments.
- Ability to influence technical direction across teams without relying solely on organizational authority.
- Preferred experience with agentic AI systems, multi-step workflows, tool-using agents, or autonomous and semi-autonomous engineering workflows.
- Preferred experience applying AI to developer productivity, code generation, testing, code review, incident management, or other SDLC stages.
- Preferred experience building internal developer platforms, engineering productivity platforms, or enterprise automation capabilities.
- Preferred experience with AI evaluation frameworks, model or agent observability, prompt and context management, retrieval architectures, and production AI quality measurement.
- Preferred experience spanning traditional software engineering and AI engineering, including backend, platform, or distributed-systems foundations.
- Preferred experience driving initiatives across multiple teams, systems, or organizational domains.
Benefits
- Medical insurance is available for employees, spouses, up to two dependent children, and parents or in-laws, subject to stated coverage limits.
- Group term and group personal accident insurance are provided, including stated coverage based on annual CTC and applicable caps.
- Leave benefits include 15 privilege days, 6 paid sick days, 6 casual leave days, 26 weeks of paid maternity leave, 1 week of paid paternity leave, a birthday day off, and paid holidays.
- Benefits include Provident Fund and Gratuity.
- Employee Assistance Program and wellness initiatives are provided.
- Employees receive ongoing learning and development opportunities and career advancement support.
- The role is remote across India; employees near the Bengaluru office are expected onsite four days per week, with the possibility of five days per week.
Categories
About Nextiva
Nextiva builds a cloud-based customer experience platform combining VoIP, unified communications, and contact center software for businesses. It sells its products as SaaS, offering an AI-powered conversation hub to manage calls, messaging, and customer interactions. Founded in 2008 and headquartered in Scottsdale, Arizona, the privately held company serves 100,000+ businesses and raised $200M from Goldman Sachs Asset Management in 2021.