Tech Lead

PRG Pakistan; Lahore; On-site; PKR 2,008,800 - 2,678,400; Full time

Job summary

PRG Pakistan is seeking a Tech Lead in Lahore, responsible for managing a team of engineers and directing the technical delivery of products. The ideal candidate will have deep expertise in software architecture and full-stack development, with a focus on integrating AI tools into daily operations.

Applicants should have 6+ years of software engineering experience, including management responsibilities. The role requires hands-on coding and collaboration with product teams for effective delivery.

Qualifications

• 6+ years of software engineering experience.
• 2+ years in a senior, lead, staff, or architect-level role.
• Hands-on line management of engineers including hiring and performance management.

Responsibilities

• Own the architecture and long-term technical direction of the product.
• Line-manage the squad, hire, mentor, and promote a high-performance culture.
• Write code and review pull requests to remain the technical anchor.

Skills

Software Architecture

Full-Stack Development

AI Tools Fluency

Team Management

Clean Code Practices

Product Acumen

Education

Bachelor’s degree in Computer Science or Engineering

Master’s degree

Tools

React/Next.js

Node.js/TypeScript

Python

Docker

AWS

Job description

Role Overview

The Tech Lead will own the end-to-end technical delivery, architecture, and engineering quality of one or more products. They will line-manage a squad of 3 to 6 full-stack engineers, partner with Product squad on scope and roadmap, and serve as the hands-on technical anchor who sets the bar for code quality, system design, and AI-assisted development. This is a senior or architect-level engineering role with people management responsibilities and strong product acumen. The Tech Lead is expected to be hands-on — writing code, reviewing PRs, leading the most consequential technical work, and orchestrating AI agents alongside the team — while also owning hiring, mentoring, performance management, and the upskilling of existing engineers into the AI-first model. The role demands deep expertise in software architecture, system design, and full-stack development; fluency with modern AI engineering tooling (Claude Code, agentic workflows, MCP, evals) as a first-class part of the daily engineering workflow; and the product judgement to translate roadmap intent into pragmatic technical execution.

Education

• Bachelor’s degree in Computer Science, Engineering, or a related discipline. Master’s is a plus.

Experience

• 6+ years of software engineering experience.
• 2+ years in a senior, lead, staff, or architect-level role (Tech Lead, Staff Engineer, Engineering Manager, Architect, or equivalent).
• Hands-on line management of 3+ engineers, including hiring, performance management & mentoring for at least 12–18 months.
• Proven track record of owning end-to-end delivery of at least one B2B SaaS product at scale, including the architecture and the team that built it.
• Demonstrable evidence of shipping with AI tools — we expect to see evidence you have shipped with AI tools, whether that is a GitHub repo, a working prototype, or a screen share walkthrough of something you built.
• Track record of shipping AI-powered features where the product was built around AI rather than a chat-widget bolted onto an existing product is a strong plus.
• Experience modernizing legacy codebases or migrating teams from a legacy stack to a modern one is a strong plus.
• Prior experience building products in medical billing, RCM, or adjacent U.S. healthcare verticals is a strong plus.
• Strong command of clean code, design patterns, testing, debugging, and code review practices. Holds a high bar regardless of whether code was written by a human or an agent.
• Hands-on across frontend, backend, database, and APIs. Can own a feature end to end without a hand off, and writes their own tests as part of the definition of done.
• Strong proficiency in modern frontend (React/Next.js or equivalent) and backend (Node/TypeScript, Python, or equivalent) stacks. Comfortable picking the right tool for the job rather than defending a favorite.
• Working experience with relational and non-relational databases, caching, message queues, and event driven architectures. Comfortable reasoning about data models for healthcare-grade workloads (PHI, audit trails, high read/write asymmetry).
• Solid working knowledge of CI/CD, containerization (Docker), and cloud deployment (AWS). Able to set up a production-grade pipeline without waiting for a separate DevOps team.
• Owns testing, observability, and on-call for the squad. Treats automated tests, logging, and monitoring as non-negotiable parts of any feature, not an afterthought.
• Demonstrated expertise designing scalable, secure, maintainable production systems; making sound trade-offs across performance, reliability, security, and cost.
• Track record of architecting and evolving complex software products end to end, including the kind of consequential decisions (build vs. buy, monolith vs. microservices, sync vs. async, data partitioning) that compound over years.
• Designs with HIPAA, PHI handling, audit logging, encryption at rest and in transit, role-based access control, and BAA-aware data flows as defaults.
• Experience evolving large codebases, paying down technical debt, and modernizing legacy systems incrementally without disrupting delivery. Comfortable making the call on rewrite vs. refactor and defending it.
• Comfortable making, defending, and revisiting architectural decisions in collaboration with engineers, product, and stakeholders.

AI Fluency

• You build with AI tools, not just use them. AI is part of your daily engineering workflow — embedded in coding, code review, debugging, design, prototyping, and architectural exploration — and you expect to see meaningful productivity gains from it, not marginal ones.
• Fluent with Claude Code and equivalent agentic engineering tools (Cursor, Copilot, Windsurf, etc.). You have shipped real production code where the agent was the primary author and you were the orchestrator.
• Comfortable running multiple agents in parallel on different parts of a feature, and managing the cognitive load that comes with it. You think about software development as orchestration of a team of agents, not a typing exercise.
• Strong context engineering instincts. You know how to set up CLAUDE.md or adjacent files, custom skills, hooks, MCP servers, and project-level guidance so an agent ships code that fits the codebase from day one.
• Treats verification as the core engineering skill. You build evals, pre-commit hooks, CI gates, and review rubrics so AI output is trustworthy by default and architectural integrity is preserved.
• Conceptual fluency with LLMs, agentic workflows, RAG, tool use, prompt design, and AI-assisted development patterns — sufficient to set, defend, and continuously raise the AI tooling bar across the squad.
• Able to build AI features into the product, not just use AI to build the product. You can scope, prototype, and ship LLM-powered features inside PRG’s products with the right safeguards (evals, guardrails, latency and cost controls, fallback paths).
• Active AI builder culture. You coach engineers into AI fluency, run the squad’s adoption of new tooling, and are the visible reference standard for what an AI-native engineer looks like.

Product Acumen

• Strong product judgement — You make trade-offs in technical scope, sequencing, and complexity against measurable user and business outcomes — not against engineering aesthetics.
• Engineer-PM peer relationship — You partner with the Product squad on roadmap, prioritization, and scope, and you push back credibly when the technical reality calls for it.
• Comfortable owning feature discovery & prioritization as well as road mapping and sequencing activities alongside the Product when needed.
• You should be comfortable prototyping an idea in code to test feasibility before committing the squad.
• Reads PRDs critically. You catch the missing edge case, the ambiguous acceptance criteria, and the scope creep before sprint planning, not after.

Strategic Thinking

• You will be expected to lead build-vs-buy evaluations, vendor selection, and architectural strategy decisions that shape our roadmap.
• You produce executive-grade decision documents — research, options, trade-offs, and a defended recommendation — and present them to leadership.
• You’re comfortable owning these decisions in regulated and ambiguous domains where there is no clean answer.

Leadership & People Management

• Prior experience line-managing an engineering team of 3+ members through a full performance cycle (hiring, goal setting, feedback, performance management, and ideally at least one promotion or exit decision).
• You should be a hands-on coach with a lead-by-example mindset. You raise the bar of every engineer reporting to you, give and receive sharp feedback, and run weekly 1:1s as a core part of the job rather than a calendar obligation.
• Comfortable assessing existing engineers against the AI-first, full-stack, senior-ownership bar, and putting staggered upskilling plans in place.
• Active role in hiring. You run technical interviews, defend hiring decisions, and are willing to leave a role open rather than lower the bar.
• Documentation-first culture. You treat written communication — design docs, decision records, post mortems, PRD reviews — as the primary tool for alignment, not meetings.
• Excellent verbal and written English. Comfortable representing the engineering function in technical reviews, executive forums, cross-team architecture discussions, and conversations with operational stakeholders (billing managers, providers). You can explain complex technical ideas and trade-offs clearly to senior leadership.

Domain Knowledge

• Familiarity with the U.S. healthcare ecosystem (medical/dental RCM, care management programs including CCM, PCM, TCM, RPM etc).
• HIPAA-grade privacy and compliance instinct in product design & technical architecture.
• Direct RCM, medical billing, or US health-tech product experience.
• EDI X12 standards (270/271, 276/277, 837P/I, 835).
• FHIR R4, HL7v2, SMART on FHIR.
• Familiarity with one or more of: athenahealth, Tebra, AdvancedMD, eClinicalWorks, Epic, Practice Fusion, Waystar, Availity, Optum, Stedi. You should possess a strong ability to proactively and quickly absorb complex, regulated and data-rich healthcare domain quickly. You’re the kind of person who, three months in, knows more about US healthcare systems than any other member in the R&D department.

Cultural Fit

• Humble, collaborative, proactive, and self driven.
• Strong ownership and accountability. Comfortable with ambiguity and shifting priorities.
• Low ego, high ownership. You raise the bar of everyone around you. You own outcomes and are comfortable jumping on calls, debugging production issues, pairing with an engineer on a hard bug, or running a customer call when needed. You are not precious about where your job ends.
• Doer, not delegator. If you see a broken flow, you find a way to fix it. You do not file a ticket and wait.
• Believes in AI first product development and is excited to shape that culture at PRG. Thinks actively about how AI can make you and the team faster, not as a buzzword but as something you build toward daily.
• Promotes these cultural values across the squad and reinforces them in how the team operates day to day.

Key Responsibilities

• Own the architecture, system design, and long-term technical direction of the product(s). Make and defend the consequential decisions; write them down.
• Line-manage the squad. Hire, mentor, set engineering standards, run weekly 1:1s, and drive a high performance, high-ownership culture.
• Stay hands-on. Write code, review PRs, lead the most critical technical work, and remain the technical anchor for the squad. The Tech Lead is not a manager-only role.
• Embed AI assisted coding tools into the daily engineering workflow. Set the squad’s standards for context engineering, agent orchestration, evals, and AI-assisted code review. Continuously raise the bar on what the squad can ship with AI as a force multiplier.
• Collaborate with the AI squad to scope and ship AI features inside the product where they unlock real user or business outcomes.
• Partner with the Product squad on scope, sequencing, and trade-offs. Translate product vision into pragmatic technical execution. Push back credibly when the technical reality demands it.
• Track progress against roadmap commitments, manage cross-squad dependencies, surface risks early, and drive on-time and high quality delivery.
• Own code quality, test coverage, performance, security, observability, on-call, and incident response. HIPAA-grade design is a default, not an audit requirement.
• For products with legacy stacks, lead the modernization effort — incrementally, without disrupting delivery.

Location

This is an on-site position based out of our Lahore office, with working hours from 1 PM to 10 PM PKT.