Technical Architect – Product Engineering

Strong Tech Lead / Staff Engineer / Lead Engineer Profiles

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Mandatory (Experience 1) - Must have minimum 6+ years of overall Software Engineering/Development experience building production backend systems.

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Mandatory (Experience 2) - Must have Tech Lead ownership, with experience setting technical direction, architecture, frameworks, or engineering standards used by other engineers.

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Mandatory (Experience 3) - Must have strong hands-on Backend development experience with deep proficiency in at least one backend programming language. (Python, Java, Golang etc)

5

Mandatory (Experience 4) - Must have strong System design/distributed systems experience, including architectural trade-offs, scalability, failure modes, reliability, and long-term maintainability.

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Mandatory (Experience 5) - Must have strong CS fundamentals in Data Structures & Algorithms, Operating Systems, and Networking, with the ability to apply them to complex backend/system problems

7

Mandatory (Experience 6) - Must have owned complex, ambiguous, or business-critical engineering problems end-to-end, demonstrating clear technical judgment, trade-offs, problem-solving, and measurable technical/business impact; not limited to feature implementation.

8

Mandatory (Experience 7) - Must have formal technical leadership experience, including mentoring Senior Engineers, conducting design/code reviews, driving engineering quality, and leading technical decisions across a team.

9

Mandatory (Experience 8) - Must be a hands-on IC + Tech Lead, with approximately 70–80% hands-on coding/engineering involvement, not a pure people-management profile.

10

Mandatory (Company) - Product Companies / Startups / B2B SaaS

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Mandatory (Education) - CS degree or equivalent (B.Tech/B.E./B.S.)

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Preferred (Skills) - Experience with Kafka/NATS/RabbitMQ, AWS, Docker/Kubernetes, CI/CD, observability, security/compliance, multi-tenant systems, and financial/billing platforms.

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

About the Role

We are seeking a hands-on Tech Lead to design, build, and integrate AI-driven systems that automate and enhance real-world business workflows. This is a high-impact role for someone who enjoys full-stack ownership — from backend AI architecture to frontend user experiences — and can align engineering decisions with measurable product outcomes.

You will begin as a strong individual contributor, independently architecting and deploying AI-powered solutions. As the product portfolio scales, you will lead a distributed team across India and Australia, acting as a System Integrator to align engineering, data, and AI contributions into cohesive production systems.

Example Project

Design and deploy a multi-agent AI system to automate critical stages of a company’s sales cycle, including:

• Generating client proposals using historical SharePoint data and CRM insights
• Summarizing meeting transcripts
• Drafting follow-up communications
• Feeding structured insights into dashboards and workflow tools

The solution will combine RAG pipelines, LLM reasoning, and React-based interfaces to deliver measurable productivity gains.

Key Responsibilities

• Architect and implement AI workflows using LLMs, vector databases, and automation frameworks
• Act as a System Integrator, coordinating deliverables across distributed engineering and AI teams
• Develop frontend interfaces using React/JavaScript to enable seamless human-AI collaboration
• Design APIs and microservices integrating AI systems with enterprise platforms (SharePoint, Teams, Databricks, Azure)
• Drive architecture decisions balancing scalability, performance, and security
• Collaborate with product managers, clients, and data teams to translate business use cases into production-ready systems
• Mentor junior engineers and evolve into a broader leadership role as the team grows

Ideal Candidate Profile

Experience Requirements

• 5+ years in full-stack development (Python backend + React/JavaScript frontend)
• Strong experience in API and microservice integration
• 2+ years leading technical teams and coordinating distributed engineering efforts
• 1+ year of hands-on AI project experience (LLMs, Transformers, LangChain, OpenAI/Azure AI frameworks)
• Prior experience in B2B SaaS environments, particularly in AI, automation, or enterprise productivity solutions

Technical Expertise

• Designing and implementing AI workflows including RAG pipelines, vector databases, and prompt orchestration
• Ensuring backend and AI systems are scalable, reliable, observable, and secure
• Familiarity with enterprise integrations (SharePoint, Teams, Databricks, Azure)
• Experience building production-grade AI systems within enterprise SaaS ecosystems

Sr. Technology Architect

Experience Range: 12–15+ years of IT experience, including 3–5+ years in leadership / people management roles.

Location: Chennai, Hyderabad, Bangalore

Qualification: B. Tech /B.E in computer science or equivalent

Minimum 10+ years of experience in Advanced Java

At least 2+ years of experience for the following areas:

• Lead and mentor full-stack development teams across multiple projects and workstreams.
• Define technical architecture, coding standards, and development best practices.
• Drive end-to-end delivery of enterprise applications using Agile methodologies.
• Oversee application design, development, testing, deployment, and production support.
• Ensure adherence to security, performance, quality, and compliance standards.
• Collaborate with clients, product owners, architects, and cross-functional teams.
• Manage resource planning, risk mitigation, technical reviews, and stakeholder communication.
• Promote DevOps, CI/CD, and automation practices to improve delivery efficiency

Must Haves-

• Strong experience in Java Full Stack Development.
• Expertise in Spring Boot and Microservices Architecture.
• Proficiency in Python, Shell Scripting, and backend development.
• Hands-on experience with SQL, Oracle, and PostgreSQL databases.
• Front-end expertise in React, Angular, HTML5, CSS3, Bootstrap, and JSP.
• Experience with Kafka or similar event-driven messaging platforms.
• Strong understanding of API Design, REST Services, and Swagger/OpenAPI.
• Experience implementing security frameworks including OAuth 2.0.
• Hands-on expertise with Jenkins, CI/CD pipelines, and DevOps practices.
• Experience with code quality and security tools such as SonarQube and Fortify.
• Proven people management, stakeholder management, and delivery leadership experience.
• Experience working in Agile/Scrum environments.

Good to Haves-

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of containerization and orchestration technologies such as Docker and Kubernetes/OpenShift.
• Experience with performance tuning, observability, and application monitoring tools.
• Telecom, OSS/BSS, or enterprise digital transformation domain experience.
• SAFe Agile, PMP, Scrum Master, or cloud certifications.
• Exposure to AI-assisted development tools and engineering productivity platforms.

Read This Before Anything Else

We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.

About CraftMyPlate

CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.

Where We Stand

Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.

Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.

The Technical Reality

Here's an honest read of the engineering problem, not a sanitized version of it.

Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.

Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.

The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.

You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.

Why This Role Exists

You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.

If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.

What You'll Own

• Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
• Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
• The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
• The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
• Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
• Technical accountability. When something breaks, you fix it. You don't escalate and wait.

Our Stack, and the Depth We Expect

Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.

Go deep here. This is where the real architecture decisions live, and where the business impact is highest:

• AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
• TypeScript, our primary language across backend and frontend.
• Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.

Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.

This Is You If

• You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
• You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
• You've made engineers around you measurably better, whether or not you've held the title for it yet.
• You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
• You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
• You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.

This Might Not Be the Right Fit If

• You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
• You'd rather receive direction than bring us architecture and AI strategy yourself.
• You haven't yet gotten hands-on with AI coding tools in your daily work.
• You're drawn more to the title than the work behind it.

If none of that sounds like you, we'd love to hear from you.

Requirements

• 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
• Prior experience leading or mentoring engineers, formally or informally.
• Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
• Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.

Compensation

Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.

If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.

Strong Python Developer profile with robust AWS exposure

2

Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS

3

Mandatory (Tech skill 1): Must have strong working knowledge of Python.

4

Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR

5

Mandatory (Tech skill 3): Must be able to write and understand REST APIs

6

Mandatory (Tech skill 4): Experience designing and architecting scalable backend applications/services on AWS, including making decisions around application architecture, APIs, databases, and AWS services

7

Mandatory (Tech skill 5): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab

8

Mandatory (Tech skill 6): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB

9

Mandatory (Tech skill 7): Must have familiarity with Linux commands and shell scripting

10

Mandatory (Skill 1): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance

11

Mandatory (Skill 2): Must have strong communication skills

12

Preferred (Tech skill 2): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools

13

Preferred (Tech skill 3): Basic understanding of CI/CD pipelines

14

Preferred (Tech skill 4): Experience with Docker or container-based applications

15

Preferred (Tech skill 5): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation

We’re on the hunt for a Principal Engineer who loves solving tough problems, mentoring others, and shaping the future of our platform. In this role, you’ll be leading the design and build of scalable systems and integrations across major cybersecurity platforms. Sometimes you’ll be deep in the code, other times you’ll be guiding teams and customers to the right solutions. If you enjoy balancing hands-on work with big-picture thinking, this could be your spot. 

About Us

At Metron Security, we help top cybersecurity companies supercharge their tools through automation and integrations. Our engineers connect and extend platforms like Splunk, IBM QRadar, ServiceNow, CrowdStrike, Cybereason, and many more. We believe in a developer-first culture where creativity, ownership, and continuous learning drive everything we do. 

Why You’ll Love Working Here

• A true developer-first environment where your ideas and technical chops matter.
• Hands-on exposure to 250+ security platforms (yep, really).
• Direct contact with customers so you can see the impact of your work right away.
• A fast-paced, growth-focused culture—but we also respect work-life balance. No weekends, and only occasional evening calls. 

What We’re Looking For 

We’re hoping to meet someone who has both deep technical expertise and natural leadership instincts. You think holistically about systems, enjoy digging into tricky problems, and can guide both teammates and customers to success.

Must-Have Skills

• Solid programming experience across multiple languages (Python, TypeScript, Java, Node.js, Angular, React, C#, C++… we’re language-agnostic and use the best tool for the job).
• Quick at learning new security platforms.
• Proven ability to design and build scalable systems, APIs, and integrations.
• Experience mentoring and leading engineering teams.
• Strong debugging and problem-solving skills in complex environments.
• Organized, reliable, and able to set and meet clear timelines.
• Comfortable working directly with customers to understand needs and design solutions.
• Familiar with cloud platforms (AWS, GCP, or Azure) and security best practices. 

Bonus Points If You

• Have experience building or leading integrations with enterprise security tools.
• Like approaching challenges with a “hacker mindset.” 
• Know your way around Docker, Kubernetes, and cloud deployments. 
• Contribute to open source or share technical insights publicly. 

What You’ll Do

• Be the face of Metron Security with our customers—collaborating on solutions and keeping communication clear.
• Bridge the gap between customers and our dev team, ensuring the right info flows both ways. 
• Mentor and train junior developers, helping them level up. 
• Step in to tackle tough technical problems when the team needs backup.
• Build and document knowledge about security platforms.
• Spot potential roadblocks early and help keep projects on track.

Who You Are

• Strategic thinker who isn’t afraid to roll up their sleeves.
• Clear communicator who collaborates openly.
• Proud of building strong, maintainable solutions that exceed expectations.
• Curious, quick learner, and always exploring new technologies.
• Positive, “let’s figure it out” teammate who lifts others up. 

At Metron Security, we’re all about helping security teams work smarter. If you’re excited to take on big engineering challenges, mentor others, and drive technical vision in a growing company, we’d love to talk.

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)

● 10–15 years of overall experience in backend engineering, with strong exposure to

Python and/or Golang.

● 3–5 years of experience managing engineering teams.

● Proven experience delivering large-scale, distributed systems in production

environments.

● Strong understanding of microservices, cloud-native architecture, and DevOps

practices.

● Hands-on background in backend engineering (able to guide teams technically, even

if not coding daily).

● Familiarity with CI/CD pipelines, observability, and performance optimization.

● Experience in financial services or high-transaction domains is a plus.

● Experience leading teams that have utilized AI-driven development practices (e.g.,

agentic coding, LLM integration) to improve productivity and innovation is a

significant advantage.

Skills

● Excellent leadership and people management abilities.

● Strong communication and stakeholder management skills.

● Ability to balance technical depth with business priorities.

● Problem-solving mindset with a focus on delivery and impact.

● Passion for building engineering culture and improving developer experience.

Strong Python Developer profile with robust AWS exposure

2

Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS

3

Mandatory (Tech skill 1): Must have strong working knowledge of Python.

4

Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR

5

Mandatory (Tech skill 3): Must be able to write and understand REST APIs

6

Mandatory (Tech skill 4): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab

7

Mandatory (Tech skill 5): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB

8

Mandatory (Tech skill 6): Must have familiarity with Linux commands and shell scripting

9

Mandatory (Skill): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance

10

Mandatory (Skill 2): Must have strong communication skills

11

Preferred (Tech skill 1): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools

12

Preferred (Tech skill 2): Basic understanding of CI/CD pipelines

13

Preferred (Tech skill 3): Experience with Docker or container-based applications

14

Preferred (Tech skill 4): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams