Senior Software Engineer (AI/ML)

Devsinc, LLC; Islamabad; On-site; PKR 1,116,000 - 1,674,000; Full time

Benefits offered by this job

Provident Fund

Medical Inpatient Facility

Medical Outpatient Facility

Paid Overtime

In-house Subsidized Lunch & Dinner

Gym Facility

Entertaining Activities

Interest Free Loan Facility

Advance Salaries

Sports Allowance

Job summary

A leading tech company in AI development is seeking a Senior Software Engineer (AI/ML) to design and build intelligent systems. The role requires expertise in machine learning, Python programming, and integrating AI agents. Responsibilities include developing production-grade AI models, optimizing pipelines, and collaborating with teams. A Bachelor's degree in Computer Science and 3+ years of experience are mandatory. Benefits include Provident Fund, medical facilities, and subsidized meals.

Qualifications

• 3+ years of software engineering experience.
• Proficiency in Python and ML frameworks.
• Experience with cloud platforms and containerization.

Responsibilities

• Design and build autonomous AI agents.
• Develop and fine-tune ML models.
• Integrate AI components into backend systems.

Skills

Python programming

Machine Learning

AI agent integration

Data processing

Cloud platforms

Containerization

Education

Bachelors Degree in Computer Science

Tools

PyTorch

TensorFlow

Docker

Kubernetes

MLflow

Job description

We are looking for a Senior Software Engineer (AI/ML) who can design, build, and scale intelligent systems — from machine learning pipelines to advanced AI agents capable of reasoning, planning, and automation.

You will work on building production‑grade AI models, integrating LLMs and tools, and designing agent architectures that interact with APIs, databases, and workflows. The role blends applied ML expertise with strong backend engineering and product‑focused problem‑solving.

Responsibilities

• Design and build autonomous or semi‑autonomous AI agents that can plan, reason, and interact with tools, APIs, or external systems.
• Implement agentic frameworks (e.g., LangChain, LlamaIndex, CrewAI, or custom orchestration systems).
• Leverage existing industry capabilities to deliver virtual assistant capabilities on top of xquic content including voice interactions.
• Optimize reasoning and retrieval pipelines using embeddings, vector databases, and prompt engineering.
• Develop, train, and fine‑tune ML models using frameworks like PyTorch, TensorFlow, or scikit‑learn.
• Work on data preprocessing, feature engineering, and model evaluation for NLP, computer vision, or predictive tasks.
• Build ML pipelines for training, deployment, and monitoring in production environments.
• Collaborate with engineering teams to integrate AI components into backend systems and APIs.
• Ensure scalable, maintainable codebases with CI/CD, observability, and cloud‑native design (AWS/GCP/Azure).
• Contribute to technical architecture and design reviews for AI‑driven features and platforms.
• Stay current with the latest in LLMs, agent frameworks, and model architectures.
• Prototype and evaluate new approaches for reasoning, tool use, and adaptive behavior in agents.
• Share learnings and mentor peers in ML and AI development best practices.

Qualifications

• Bachelors Degree in Computer Science or related fields.
• 3+ years of experience.
• Strong programming skills in Python (mandatory); proficiency with PyTorch, TensorFlow, or transformers‑based models.
• Experience in building or integrating AI agents (LangChain, LlamaIndex, CrewAI, custom frameworks).
• Strong grasp of ML model lifecycle — data processing, model training, evaluation, deployment, and monitoring.
• Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
• Familiarity with API integrations, microservices, and asynchronous systems.
• Strong understanding of vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) and retrieval architectures.
• Solid software engineering fundamentals — testing, version control, and system design.
• Experience with LLM fine‑tuning, prompt optimization, or RAG (Retrieval‑Augmented Generation) systems.
• Familiarity with multi‑agent systems and coordination mechanisms.
• Knowledge of MLOps tools (MLflow, Kubeflow, Sagemaker, Vertex AI).
• Experience in AI system observability, evaluation metrics, and continuous learning loops.
• Exposure to reinforcement learning or self‑improving agent architectures.

Benefits

• Provident Fund
• Medical Inpatient Facility
• Medical Outpatient Facility
• Paid Overtime
• In‑house Subsidized Lunch & Dinner
• Gym Facility
• Entertaining Activities
• Interest Free Loan Facility
• Advance Salaries
• Sports Allowance