AWS AI Engineer

CodeNinja is expanding its Cloud & AI practice and is seeking an AWS AI Engineer. This role involves architecting and implementing AI/ML and Generative AI solutions on AWS, supporting AWS partnership accreditation, engaging in presales activities, and contributing to internal knowledge building. It's a high-impact position combining hands-on engineering, client interaction, and AWS ecosystem expertise to innovate and automate for global clients.

Must Have

• Architect and implement AI/ML solutions using AWS services (SageMaker, Bedrock, Comprehend, Rekognition, Lex, Kendra, Lambda, Step Functions, S3, RDS, DynamoDB, OpenSearch).
• Develop and optimize ML pipelines.
• Build and deploy RAG systems and inference workflows.
• Contribute to customer success stories and required evidence for AWS tier progression.
• Support AWS scorecard requirements.
• Join presales calls with sales/partnership stakeholders and lead technical discovery.
• Translate business requirements into AWS-native solution designs and implementation plans.
• Build PoCs and demos to support sales cycles.
• Prepare technical proposals, architecture diagrams, and effort estimates.
• Create and maintain an internal AI Practice Hub.
• Develop training material and run internal sessions on GenAI, MLOps, and AWS AI services.
• Collaborate with Cloud/Data/DevOps/MLOps teams on delivery and standards.
• 4+ years of hands-on experience delivering AI/ML solutions on AWS.
• Strong Python skills (APIs, Lambda handlers, ML pipelines; FastAPI preferred).
• Experience with ML frameworks: PyTorch / TensorFlow / Scikit-learn.
• Practical experience building RAG systems, embeddings, and retrieval pipelines.
• Familiarity with vector stores such as FAISS, OpenSearch, Pinecone, Chroma.
• Strong client-facing communication and presentation skills.
• Strong documentation discipline (architecture notes, runbooks, playbooks).
• Ability to translate ambiguous needs into clear technical solutions.

Good to Have

• Experience with GenAI providers/models (e.g., OpenAI, Anthropic, Llama).
• Experience with SageMaker Pipelines / Kubeflow / MLflow.
• Experience deploying AI-backed APIs or chatbot systems in production.
• Prior consulting or presales experience.

Perks & Benefits

• Provident Fund
• Gym Membership
• Leaves as per the company policy
• Company-paid trips
• Easy Loan Facility for Employees
• Yearly increment
• Maternity Benefits (Leaves & WFH)
• Health Insurance (Maternity covered) – includes spouse and parents (till age 80)

Description

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About the Company

CodeNinja is a global AI and engineering services company helping enterprises build, scale, and operate intelligent systems. With 350+ engineers across four continents and 400+ successful deployments, CodeNinja enables organizations to harness artificial intelligence through Global Capability Centers, Work AI, Physical AI, and AI Labs. Recognized among Pakistan’s fastest-growing AI firms and a multi-award recipient on Clutch, CodeNinja empowers over 250 clients worldwide to innovate, automate, and compete in the intelligence economy.

Role Overview

CodeNinja is building its next-generation Cloud & AI practice as part of our journey toward becoming an AWS AI Standard Tier Partner. We are hiring an AWS AI Engineer to support AWS partnership accreditation, design and deliver AI/ML and Generative AI solutions on AWS, and enable presales and internal capability building.

This is a high-impact role combining hands-on engineering, client-facing engagement, and AWS ecosystem expertise.

Key Responsibilities

1) AWS AI & ML Solution Engineering

• Architect and implement AI/ML solutions using AWS services including:

• Amazon SageMaker (training, tuning, deployment)
• Amazon Bedrock (LLMs, GenAI orchestration)
• Comprehend, Rekognition, Lex, Kendra
• Lambda, Step Functions (orchestration)
• S3, RDS, DynamoDB, OpenSearch (data backbone)

• Develop and optimize ML pipelines (ingestion, preprocessing, feature engineering, deployment).
• Build and deploy RAG systems and inference workflows.

2) Support AWS AI Partnership Accreditation

• Contribute to customer success stories and required evidence for AWS tier progression.
• Support AWS scorecard requirements (training completion, technical documentation, artifacts).
• Build reusable templates, architectures, accelerators, and reference implementations.
• Maintain practice documentation (playbooks, architectures, runbooks).

3) Presales & Customer Engagement

• Join presales calls with sales/partnership stakeholders and lead technical discovery.
• Translate business requirements into AWS-native solution designs and implementation plans.
• Build PoCs and demos to support sales cycles.
• Prepare technical proposals, architecture diagrams, and effort estimates.

4) AI Knowledge Base & Internal Enablement

• Create and maintain an internal AI Practice Hub (e.g., Notion):

• Service catalog, case studies, best practices
• Accelerators, reusable components, reference architectures

• Develop training material and run internal sessions on GenAI, MLOps, and AWS AI services.

5) Cross-Functional Collaboration

• Collaborate with Cloud/Data/DevOps/MLOps teams on delivery and standards.
• Partner with Sales and Marketing on AI GTM collateral and demos.
• Provide inputs to AI practice roadmap, delivery frameworks, and governance.

Requirements

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Required Skills & Experience

Technical

• 4+ years of hands-on experience delivering AI/ML solutions on AWS.
• Strong knowledge of:

• SageMaker, Bedrock, Lambda, Step Functions
• S3, DynamoDB, OpenSearch
• IAM, CloudWatch, CloudFormation/Terraform

• Strong Python skills (APIs, Lambda handlers, ML pipelines; FastAPI preferred).
• Experience with ML frameworks: PyTorch / TensorFlow / Scikit-learn.
• Practical experience building RAG systems, embeddings, and retrieval pipelines.
• Familiarity with vector stores such as FAISS, OpenSearch, Pinecone, Chroma.
• Exposure to MLOps tooling (e.g., MLflow, containerization, Kubernetes).

Soft Skills

• Strong client-facing communication and presentation skills.
• Strong documentation discipline (architecture notes, runbooks, playbooks).
• Ability to translate ambiguous needs into clear technical solutions.
• Comfortable collaborating with engineering, sales, and leadership stakeholders.

Nice to Have

• Experience with GenAI providers/models (e.g., OpenAI, Anthropic, Llama).
• Experience with SageMaker Pipelines / Kubeflow / MLflow.
• Experience deploying AI-backed APIs or chatbot systems in production.
• Prior consulting or presales experience.

Why Join CodeNinja

• Work on real-world AI and cloud solutions for global clients.
• Collaborate with high-performing, cross-functional teams.
• Grow your career in a fast-scaling, innovation-driven environment.

Disclaimer: CodeNinja is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, & performance. Female and minorities are strongly encouraged and preferred to apply for the role.

Benefits

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• Provident Fund
• Gym Membership
• Leaves as per the company policy
• Company-paid trips
• Easy Loan Facility for Employees
• Yearly increment
• Maternity Benefits (Leaves & WFH)
• Health Insurance (Maternity covered) – includes spouse and parents (till age 80)