Senior Director

Straive; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Straive in India invites a Sr. Director – AI & Software Engineering to define technical direction, resolve complex challenges, and drive solutions from prototype to secure, scalable production.

The role combines architecture oversight with hands-on execution leadership, targeting improved enterprise AI economics through frontier, open-source, and smaller models. This leader stays close to the technology, guides design and code reviews, mentors teams, and is accountable for high-stakes

Qualifications

• 12–18 years of experience across software engineering, architecture, data platforms, AI/ML or related roles.
• Proven ownership of enterprise-grade software, data, or AI products from architecture through production.
• Strong hands-on engineering background, preferably in Python and modern backend/frontend technologies.
• Practical GenAI experience spanning RAG, vector search, agentic workflows, model evaluation, safety controls, and production monitoring.

Responsibilities

• Own engineering standards across architecture, development, testing, deployment, security, observability, and documentation.
• Define scalable, reliable AI/GenAI architectures based on accuracy, cost, latency, privacy, and deployment needs.
• Lead selection, evaluation, fine-tuning, optimization, and deployment of frontier, open-source, small, and domain-specific models.

Skills

Hands-on technical leadership

Python

GenAI / AI architectures

Distributed systems

Cloud-native / microservices

Mentoring

Code reviews / architecture reviews

Tools

Kubernetes

Docker

CI/CD tooling

Job description

Sr. Director – AI & Software Engineering

India |Data, Analytics & AI | Full-time| Hands-on technical leadership

Straive is seeking a hands-on technology leader to serve as the senior technical authority for our AI, analytics, and software engineering solutions.

About the Role:

You will set technical direction, resolve complex engineering challenges, and move solutions from prototype to secure, scalable production. The role combines architecture and execution leadership including a mandate to improve enterprise AI economics through fit-for-purpose frontier, open-source, and smaller models.

This is not a conventional delivery-governance role. You will remain close to the technology, lead critical design and code reviews, mentor teams, and take accountability for high-stakes technical outcomes.

Key Responsibilities

• Own engineering standards across architecture, development, testing, deployment, security, observability, and documentation.
• Ensure prototypes have a credible production path; introduce architecture and code reviews, automated testing, quality gates, and release-readiness checks.
• Close gaps in scalability, performance, reliability, maintainability, and security from design through deployment.

2. AI Architecture and Economics

• Define scalable, reliable, and cost-effective AI/GenAI architectures based on accuracy, cost, latency, privacy, and deployment needs.
• Lead selection, evaluation, fine-tuning, optimization, and deployment of frontier, open-source, small, and domain-specific models.
• Reduce operating cost through model routing, caching, quantization, batching, retrieval and prompt optimization; design robust RAG and agentic systems with evaluation, guardrails, monitoring, and human oversight.

3. Technical Architecture and Platforms

• Serve as the final escalation point for complex architecture, performance, security, and deployment issues.
• Guide modular applications, APIs, microservices, data pipelines, AI services, cloud infrastructure, and enterprise integrations.
• Promote reusable components and strong cloud-native, CI/CD, observability, data governance, and secure-development practices.

4. Team Capability

• Mentor architects, engineering leads, data scientists, and developers through design reviews, code reviews, and technical workshops.
• Build independent problem-solving capability, identify skill gaps, and support targeted hiring and development.
• Create a culture of engineering ownership, technical rigor, experimentation, and continuous improvement.

5. Client Solutioning and Innovation

• Partner with commercial, consulting, and delivery teams on client workshops, proposals, due diligence, and solution design.
• Assess feasibility, architecture, effort, risk, and operating cost; translate business problems into pragmatic technical roadmaps.
• Develop reference architectures and accelerators that strengthen Straive's differentiation and delivery speed.

Required Experience and Qualifications

• 12–18 years across software engineering, architecture, data platforms, AI/ML, or related roles, including experience in a startup, product company, or similarly fast-moving environment.
• Proven ownership of enterprise-grade software, data, or AI products from architecture through production adoption.
• Strong hands-on engineering background, preferably in Python and modern backend/frontend technologies.
• Practical GenAI experience spanning RAG, vector search, agentic workflows, model evaluation, safety controls, and production monitoring.
• Strong command of distributed systems, APIs, microservices, cloud-native architecture, enterprise integration, and at least one major cloud platform.
• Working knowledge of containers, Kubernetes, CI/CD, infrastructure automation, observability, secure development, and modern data platforms.
• Demonstrated ability to improve solution cost, latency, scalability, reliability, and engineering quality.
• Experience mentoring senior technical professionals and communicating complex decisions to business and client leaders.

Preferred Experience

• Multi-tenant platforms, reusable AI accelerators, MLOps/LLMOps, model governance, or regulated and security-sensitive environments.
• Technical pre-sales, client workshops, proposals, solution estimation, and technical due diligence.
• A track record of taking multiple AI or software products from concept to sustained production use.

Leadership Profile

• Hands-on and accountable: Stays close to code and architecture and drives critical issues to resolution.
• Commercially pragmatic: Balances technical ambition with client value, speed, maintainability, and cost.
• Constructive challenger: Identifies weaknesses early, challenges assumptions, and raises engineering standards.
• Capability builder: Develops strong, independent teams rather than becoming the sole source of expertise.

Why Join Straive?

You will shape how enterprise-grade AI solutions are architected, built, and scaled with the mandate to influence technical strategy, strengthen engineering practices, develop high-performing teams, and deliver differentiated solutions for global clients.