SDE IV

JOB DESCRIPTION

Lead Engineer

Ahmedabad, India | Around 5 years of experience

Salary is open for the right candidate.

About the role

A growing healthcare technology startup is building AI-native hospital management systems and

healthcare products for emerging markets. You’ll set technical direction, lead the engineering team, and

stay hands-on with the code that ships.

What you’ll do

Set technical direction. Make architecture decisions, weigh trade-offs, and build systems that stay

reliable as requirements evolve.

Ship production software. Write, review, test, and debug code, and own the quality of what ships.

Lead the team. Break complex problems into deliverable work, mentor engineers, and take responsibility

for delivery.

Use AI coding agents. Give agents the context to tackle substantial engineering work, then critically

review, test, and debug their output.

Work with healthcare teams. Learn their workflows and turn complex requirements into dependable

software.

What you’ll bring

Production ownership. Around five years of experience, including meaningful ownership of complex

systems or products in production. Experience can be flexible for exceptional candidates.

Technical depth. Strong ability in mathematics, algorithms, or machine learning, demonstrated through

competitions, research, or demanding systems you’ve built and deployed.

Engineering leadership. Examples of architecture decisions you owned, engineers you mentored, and

work your team delivered.

AI-assisted development skills. A workflow you can demonstrate, including how you spot incorrect

assumptions, test changes, and debug failures.

Initiative and judgment. You learn quickly, tackle unfamiliar problems independently, and get working

software into users’ hands.

How to apply

Send your CV or LinkedIn profile to the recruiter who shared this brief. Include one or two examples of

your strongest technical work, a team leadership example, and an example of your AI coding workflow.

Highlight your own contribution and share only material you’re permitted to disclose.

Please include your salary expectations, notice period, and availability to work in Ahmedabad.

Director of Engineering (AI Solutions & Delivery)

About the Role

We are looking for a Director of Engineering to lead engineering execution and delivery across our enterprise AI solutions. This role combines strong engineering leadership with operational discipline, ensuring AI products move from technical design to production with predictable timelines, high quality, and reliable performance.

You will lead Engineering Managers and Tech Leads, oversee multiple engineering teams, and drive delivery excellence across AI-powered applications and platforms. The focus is on execution, technical quality, and organizational accountability, ensuring teams deliver scalable, production-ready AI systems without compromising reliability or engineering standards.

Key Responsibilities

1. Engineering Delivery & Execution

• Own engineering delivery schedules, translating product roadmaps into achievable sprint plans and release milestones.
• Establish measurable delivery targets, aiming for at least 85% on-time delivery across engineering teams.
• Identify and resolve cross-team dependencies, technical bottlenecks, and resource constraints before they affect delivery.
• Drive engineering process improvements across Agile development, CI/CD, automated testing, and release management.
• Monitor delivery metrics, sprint commitments, and release readiness to maintain predictable execution.

2. AI Quality, Evaluation & Governance

• Establish automated AI evaluation pipelines to measure hallucinations, relevance, groundedness, and contextual accuracy before production releases.
• Define quality benchmarks and evaluation criteria for LLM-powered applications and AI-driven workflows.
• Implement safety mechanisms, validation filters, circuit breakers, and human-in-the-loop fallbacks to manage unpredictable AI outputs.
• Oversee RAG pipelines, vector databases, data ingestion, and retrieval mechanisms to maintain accurate, reliable, and compliant context.
• Reduce production AI quality regressions through continuous evaluation, monitoring, and feedback loops.

3. Architecture, Scalability & Reliability

• Oversee the architecture of distributed systems and cloud-native applications to support scalability, availability, and performance.
• Drive reliability targets, including 99.9% uptime and low time-to-first-token (TTFT) latency for applicable AI applications.
• Partner with Staff and Principal Engineers to design resilient systems, including fallback mechanisms for model API failures, timeouts, and rate limits.
• Establish engineering standards for code reviews, observability, automated integration testing, and security compliance.
• Ensure production systems meet defined service-level objectives (SLOs) and performance benchmarks.

4. Engineering Leadership & Team Development

• Lead and develop Engineering Managers and Tech Leads, establishing clear ownership, accountability, and delivery expectations.
• Build a high-performance engineering culture focused on technical excellence, collaboration, and continuous improvement.
• Partner with Talent Acquisition to attract, assess, and hire strong software engineering and AI talent.
• Align engineering resources with business priorities, delivery commitments, and technical requirements.
• Address performance and execution challenges while maintaining team engagement and engineering quality.

Success Metrics: First 90 Days

First 30 Days

• Assess existing engineering workflows, delivery pipelines, and release processes.
• Establish baseline AI evaluation criteria and identify gaps in production quality.
• Take ownership of engineering delivery across teams and align expectations with Engineering Managers and Tech Leads.

First 60 Days

• Implement automated AI evaluation frameworks and establish measurable quality benchmarks.
• Improve cross-team coordination and resolve key delivery dependencies.
• Establish consistent sprint planning, release cadences, and delivery reporting.

First 90 Days

• Achieve at least 85% sprint commitment completion.
• Demonstrate measurable reductions in production AI quality regressions.
• Improve system reliability and stabilize latency against defined performance targets.
• Establish clear accountability and predictable delivery practices across engineering teams.

Qualifications & Requirements

• Experience: 14+ years in software engineering, including at least 5 years managing Engineering Managers or Tech Leads in enterprise or high-growth environments.
• AI/ML Expertise: Hands-on experience delivering AI-powered systems involving LLMs, RAG architectures, vector databases, prompt engineering, or model fine-tuning workflows.
• Engineering Delivery: Proven ability to lead multiple engineering teams and deliver complex technical initiatives from design through production launch.
• System Architecture: Experience with distributed systems, cloud-native backend infrastructure, and scalable APIs across AWS, GCP, or Azure.
• AI Quality & Reliability: Understanding of AI evaluation frameworks, production monitoring, hallucination mitigation, guardrails, and system reliability.
• Delivery Management: Strong experience with Agile methodologies, CI/CD, release planning, and engineering performance metrics.
• Leadership: Ability to establish accountability, manage competing priorities, and deliver against ambitious deadlines without compromising quality or team morale.

What Success Looks Like

The successful candidate will establish predictable engineering delivery, improve the quality and reliability of production AI systems, and build a culture of ownership across engineering teams. They will combine technical judgment with execution-focused leadership to ensure AI solutions are delivered on schedule, operate reliably, and meet enterprise expectations.

If you are passionate about building high-performing engineering teams and delivering enterprise-grade AI solutions at scale, we would like to hear from you.

About the role

You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.

Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office

What you will do

Technology & product leadership

• Define and drive the technology vision, architecture and long-term platform roadmap.
• Oversee the architecture, design and delivery of highly scalable enterprise systems.
• Ensure engineering excellence, velocity and reliability across the product lifecycle.

Engineering & platform management

• Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
• Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
• Oversee operational effectiveness, including uptime, production reliability and cost optimisation.

Innovation & AI strategy

• Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
• Own the GenAI/LLM solutions architecture.
• Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
• Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
• Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.

Technical leadership

• A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
• Collaborate with executive leadership on business strategy, client requirements and product delivery.
• Build, mentor and scale high-performing engineering teams with a growth mindset.
• Establish a strong technology culture grounded in ownership, innovation and continuous learning.

What success looks like

• Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
• Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
• Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.

Qualifications & experience

• Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
• A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
• Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
• Proven leadership in defining and executing technology strategy and platform roadmaps.
• Extensive cloud-native engineering experience with Azure, AWS and GCP.

Technical expertise

• Strong full-stack engineering background (Java, Python, JavaScript frameworks).
• Expertise with JS frameworks such as React, Angular and Node.js.
• Experience building and scaling distributed systems and microservices.
• Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
• Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).

Behavioural & leadership competencies

• Product and delivery management expertise, end to end, including delivery and customer support.
• Excellent communication, with the ability to influence executive stakeholders.
• High technical proficiency combined with strong business acumen.
• Strong analytical and decision-making skills.

About the company

The client is the home base for hardware engineers. They give the teams building robots, rockets, medical devices, and the next generation of physical products a single place to move fast without breaking things, turning CAD chaos into a system of record engineers actually love to work in. We're profitable, post-Series A, and growing our Hyderabad engineering team.

About the role

We're looking for a tech lead to set the technical direction for a growing team and raise the bar for everyone around them. This is a hands-on leadership role: you'll still write production code, but your largest impact comes through architecture, mentorship, and the standards you instill. You own outcomes for a team, not just your own commits. 

What you'll do

• Lead the technical direction of a team building across our TypeScript/React + Node.js + AWS stack
• Drive architecture decisions, document tradeoffs, and align the team on a clear technical path Mentor engineers through code review, pairing, and guidance, growing them toward strong production ownership
• Set and uphold standards for code quality, testing, and operational rigor
• Stay hands-on: write production code on the highest-leverage and hardest problems
• Partner with product and leadership to scope work, manage technical risk, and deliver predictably
• Be accountable for the reliability and maturity of the systems your team owns in production

What we're looking for

• Demonstrated technical leadership: you've set direction for a team and elevated those around you
• Strong full-stack proficiency in TypeScript, React, and Node.js, plus solid AWS depth
• A track record of shipping to production and owning systems in operation, and of holding a team to that same standard
• Strong architectural judgment: you decompose ambiguous problems, weigh tradeoffs, and make decisions others can build on
• Excellent communication: you keep your team aligned and stakeholders informed, and you surface risk early
• Comfort leading in a fast-paced, high-ownership early-stage environment 

Why choose us?

• The teams building advanced hardware and the robots, machines, and devices shaping the future run
• Direct access to founders; you'll help shape product and engineering direction, not just execute tickets
• Fast feedback loops: what you build is in front of customers in days, not quarters
• Profitable at Series A, so you get startup upside without the constant fundraising-survival anxiety
• Competitive compensation and meaningful equity
• Bi-yearly appraisal cycles
• Upto 20% Bonus based on performance
• Monthly Swiggy vouchers
• Flexibility with work hours

Senior Technical Manager

Primary objective: Own engineering teams, architecture, delivery governance and successful execution of product and AI initiatives across DocTutorials.

Location

Hyderabad / Chennai

Employment

Full-time

Experience

10+ years

Role Summary

The Senior Technical Manager combines technical leadership, people management, product delivery and project execution. The role is accountable for team outcomes, engineering quality, timelines, production stability and the disciplined delivery of AI projects.

Key Responsibilities

1. Technology and Architecture Leadership

·       Provide direction for Python FastAPI, React/Next.js, data, cloud and AI architectures.

·       Review solution designs for security, scalability, maintainability, performance and cost.

·       Define engineering standards and resolve complex cross-team technical risks.

·       Remain technically hands-on through architecture reviews, critical code reviews and incident debugging.

2. People and Delivery Management

·       Lead, mentor and develop engineering teams with clear goals and accountability.

·       Own estimation, capacity, execution, dependencies, risks, releases and delivery recovery plans.

·       Conduct regular one-to-ones, performance reviews, coaching and skill-development planning.

·       Work with Product, QA, DevOps and stakeholders to deliver measurable product outcomes.

3. AI Project Execution

·       Assess AI use cases for feasibility, data readiness, risk, cost and measurable value.

·       Lead delivery of LLM, RAG, agentic and AI-assisted product initiatives from PoC to production.

·       Ensure evaluation, human validation, security, privacy, observability and rollback controls.

·       Prevent isolated demos, uncontrolled AI usage and dependency on individual engineers or vendors.

Required Skills and Experience

·       10+ years in software engineering with significant technical and people leadership experience.

·       Strong understanding of Python/FastAPI, React/Next.js, APIs, databases, cloud and distributed systems.

·       Proven ownership of product delivery, project planning, risk management and production operations.

·       Experience hiring, mentoring, evaluating and developing engineering teams.

·       Strong knowledge and execution experience across AI/ML, LLM, RAG or agentic-AI projects.

·       Practical understanding of Generative AI, LLMs, RAG, Agentic AI and responsible AI use relevant to the role.

·       Ability to use approved AI tools productively while protecting source code, credentials, learner data and organisational information.

·       Commitment to human review, testing, security validation and traceability for AI-assisted outputs.

Good-to-Have Experience

·       EdTech or medical-learning product experience.

·       AWS, Kubernetes, DevSecOps, MLOps or LLMOps.

·       Experience scaling teams and platforms through major transformation.

How Success Will Be Measured

·       Delivery becomes predictable with risks identified early.

·       Engineering quality, security and production stability improve.

·       AI projects progress from validated use cases to reliable production outcomes.

·       Team capability, ownership, engagement and succession strength increase.

·       Work consistently delivers measurable outcomes and business value—not merely completion of assigned tasks or activities.

Expected mindset: Own the outcome, use AI responsibly, communicate risks early and deliver secure, measurable value for DocTutorials and its learners.

• We are seeking a high-velocity Senior Technical Lead with an overall experience
• of 12+ years in software engineering who thrives in an environment of autonomy
• and rapid iteration. At Nomiso, we don't just write code; we build resilient systems.
• This role is designed for a builder who embraces our core philosophy: Build, Ship,
• Measure, Improve. You will be responsible for taking features from a raw concept
• to a live environment, ensuring that every deployment delivers high technical
• excellence and system stability. You are not just an executor; you are a technical
• owner and system architect who understands that the "Ship" is only the midpoint of the system lifecycle.

What We’re Looking For (Who You Are)

● AI Systems Architect (5+ years in AI - LLM, RAG, Context Engineering, React, Prompt): You've shipped multiple production LLM systems at scale. Deep understanding of RAG, fine-tuning, prompt optimization, inference scaling, and cost management. You make pragmatic trade-offs between

accuracy, latency, and cost.You are accountable for the high quality solution and timely shipment of the feature as per committed timeline.

● Technical Lead Manager (TLM): In this role you will do 70% technical work and 30% people management & project management work. You've led engineering teams (4-8+ engineers). You grow engineers through mentoring, clear feedback, and ownership. You balance shipping speed with technical excellence and team development.

● The "Builder" Mentality: You have a bias toward action. You prefer a

working feature over a perfect specification and understand the value of

getting software into the hands of users early. You will not leave the tech

debt for a long time. Tech debt will be continuously addressed as product matures.

● Pragmatic Architect: You choose the right tool for the job, balancing

long-term scalability with the immediate need for speed and delivery.

● Cross-functional engagement: Partner with Product, QA, and Solution

Architects, Project manager to align execution with outcomes

● Continuous Learner: You view "Improvement" as a mandatory phase, not an optional one. You are eager to refactor and pivot based on objective evidence.

Requirement

AI Expertise

• LLM APIs (OpenAI, Anthropic, Hugging Face), model selection and trade-offs. RAG pipeline architecture, fine-tuning strategies, prompt engineering, Agentic patterns, multi-step reasoning, reliability under uncertainty

Fullstack depth

● Backend: Python (FastAPI,

Django) and Node.js (Express,

Nest.js)

● Frontend: React (TypeScript,

state management, performance

optimization)

● Databases: PostgreSQL (query

optimization, schema design,

scaling)

● Infrastructure: AWS (Lambda,

ECS, RDS, S3), Docker, CI/CD,

monitoring

Leadership

● Managed engineering teams

(4-8+ engineers)

Category Requirement

● Experience mentoring and

growing engineers

● Track record of building

high-performing teams

● Comfortable with ambiguity and

rapid decision-making

Experience 12+ years in a technical-focused

engineering environment.

Education Degree in CS or equivalent professional

experience.

You will operate within a cross-functional squad, collaborating daily with Solution

Architects and other engineering peers. You will ensure that features are released

safely and frequently, and own the success of the product, by analysing the

insights and user feedback. Our hierarchy is flat; you are expected to provide

technical leadership and mentorship to junior peers while having a direct line of

communication with leadership regarding technical strategy and technical debt.

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

• Own the overall product architecture and technical roadmap.
• Design and build scalable, secure, and highly available enterprise applications.
• Lead the design and implementation of new product features from concept to production.
• Remain hands-on with coding and contribute to critical product components.
• Drive architecture reviews, code quality, performance optimization, and engineering best practices.
• Lead cloud architecture, security, scalability, and DevOps initiatives.
• Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
• Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

• 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
• Strong hands-on expertise in Python and modern backend frameworks.
• Deep experience with AWS services and cloud-native application architecture.
• Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
• Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
• Strong knowledge of SQL and NoSQL databases.
• Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
• Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
• Strong analytical, problem-solving, and decision-making skills.

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

We’re Hiring | Technology Lead – Java & AWS

Locations: Kochi | Trivandrum | Bangalore

Experience: 15–18 Years

Key Skills: Java, AWS, AI/ML

What We’re Looking For

Strong hands-on expertise in Java and enterprise application development.

Solid experience with AWS and cloud-based architectures.

Practical experience implementing AI/ML solutions.

Expertise in solution architecture, system integration, and scalable application design.

Proven ability to lead technical initiatives while remaining actively involved in coding, design, and troubleshooting.

Experience delivering end-to-end enterprise solutions.

Technogise provides software engineering services. We build software for clients who buy the quality of the work and business outcomes rather than the headcount. Over the last year, we built an AI-augmented way of delivering it and won business on that basis. This role grows that business and keeps the capability behind it ahead of what we offer.

Why this role exists

You’ll use your technology and engineering expertise to grow the business and strengthen the organisation’s capabilities, with AI at the core.

This includes marketing, outreach, account growth, and hiring.

You’ll execute, support teams, and improve processes wherever your expertise can make the biggest impact.

What you will own: growing the business

Pre-sales and solutioning. Work with the sales side on accounts in the presentation and proposal stage: understand the customer's problem, shape the technical solution, size it, and present it. You will be in front of customers, and you need to hold a technical conversation with them without a manager translating.

Accounts and the commercial side. You need to understand how a proposal becomes a staffed team, what bench and utilisation cost, why a delivery slip is a commercial problem before it is a technical one, and how an account grows from one team to three. You will be asked for a view on pricing and staffing shape, not only on architecture.

Team Readiness & Capability Building. Drive cross-technology training and forward-looking learning initiatives to prepare teams for emerging technologies, AI adoption, and evolving client needs.

Thought Leadership & Sales. Drive technical thought leadership through case studies, deep dives, and blogs that showcase our expertise and build credibility. Translate this content into marketing, lead generation, and sales opportunities by helping prospects understand how we solve their challenges. Use AI to scale content creation while ensuring technical depth, quality, and business relevance.

Hiring. Take the interviews where the technical call is hard, keep the bar aligned with the work we are selling now, and give the recruitment team a way to read a candidate's AI claims that is better than counting tool names on a resume.

What you will own: Raising what we can do

Capability and enablement. Keep our AI-augmented engineering practice up to date and drive its adoption through maturity assessments, training, hands-on team support, and evaluation of new tools. Help engineers, recruitment, and people teams understand and build the AI capabilities we need..

Capability we can sell. Turn things we can do into things we can offer. A new service line starts as an internal spike, becomes a demo, then a proposal. Recent examples are agentic AI engagements, infrastructure automation, and data engineering.

Technical cover on delivery. Support multiple active engagements by helping delivery leads resolve tough design decisions, validate estimates, review code and architecture, and address quality issues early. Stay independent of individual teams to provide an objective, cross-project perspective. Champion AI while ensuring the focus remains on delivering real outcomes.

What we are looking for

• Genuinely strong hands-on engineering. You still read and write code, and you can hold your own in a design review with the sharp engineers in the room. This one is not negotiable.
• An instinct for the business of a services firm: proposals, staffing, utilisation, and how repeat business actually happens.
• Hands-on with LLM-based development: coding agents, agentic workflows, retrieval over private data, and judging what a model actually produced
• Comfortable in front of a customer, including one who is technical and sceptical
• A teaching instinct. You like making other engineers better and you have evidence of having done it.
• Judgement about quality. You can tell the difference between a demo that works and a system that will hold
• Able to work through functions you do not run, since marketing, recruitment and sales own their own work and you make it sharper
• Comfortable being measured by business you helped win and capability you raised, rather than by software you personally shipped

Useful but not required: exposure to data engineering, a public body of writing or open-source work, experience running training for engineers.