ai security engineer

Information Technology Senior Management Forum

<div><div><p>Posted Date</p>
<p>6/15/2026</p>
</div><div><p>Description</p><p></p><div><p><b><br>
Regular or Temporary:</b></p>
Regular<p><b>
Language Fluency: </b>English (Required)</p><p><b>
Work Shift:</b></p>
1st shift (United States of America)<h4 class="jobSectionHeader"><b>
Please review the following job description:</b></h4>
***This role is 5 days a week in the Atlanta or Charlotte Office***<br>
<br>
Responsible for developing and maintaining the technical IT/cyber security capabilities necessary for safeguarding the firm's information systems and The Cybersecurity Engineer (AI Cloud Security) is part of Truist&rsquo;s AI Security Engineering function and is responsible for designing, engineering, deploying, and operating security controls for AI, ML, and Generative AI systems across cloud platforms.<br>
<br>
This role focuses on hands on engineering, enabling secure AI usage through cloud-native security controls, automation, and infrastructure as code, and operationalizing enterprise AI security standards. Engineers in this role work closely with AI platform teams, cloud engineering, governance, and risk partners to ensure AI systems are secure by design, compliant by default, and scalable across the enterprise.<br>
<br>
Designs and develops advanced technical and cybersecurity capabilities across all phases of the software development lifecycle, including threat modeling, security testing, and penetration testing. Plans, builds, and enhances cybersecurity technologies by baselining systems, analyzing trends, and preparing for future requirements to deliver reliable, scalable, and secure technology solutions with major impact on the job area.<p><b>
ESSENTIAL DUTIES AND RESPONSIBILITIES</b></p><p>
Following is a summary of the essential functions for this role. Other duties may be assigned as needed.</p><p><b>
AI &amp; Cloud Security Engineering</b></p><ul><li>
Engineer and deploy security controls for AI/ML and Generative AI systems, including model-level, data-level, and platform-level protections.</li><li>
Implement AI guardrails and safety controls (e.g., prompt injection defenses, content safety filters, policy enforcement, model access controls).</li><li>
Support secure AI platform onboarding for internal teams, ensuring alignment with Truist AI Security Standards and Review Processes.</li><li>
Perform technical security assessments of AI systems and cloud-hosted AI services.</li></ul><p><b>
Infrastructure as Code &amp; Automation</b></p><ul><li>
Design and implement Infrastructure as Code (IaC) using Terraform and CloudFormation to deploy AI security controls consistently.</li><li>
Build and maintain CI/CD pipelines (GitLab) for security tooling, guardrails, and configuration-as-code.</li><li>
Automate operational workflows using Python and scripting to reduce manual security operations.</li></ul><p><b>
Cloud Platform Security</b></p><ul><li>
Engineer secure, scalable cloud environments supporting AI workloads across AWS and Azure.</li><li>
Implement and integrate cloud security tooling (e.g., Wiz) to provide visibility and control over AI assets.</li><li>
Secure containerized and orchestrated workloads supporting AI pipelines (ECS, EKS, Kubernetes).</li></ul><p><b>
Collaboration &amp; Enablement</b></p><ul><li>
Partner with AI platform teams, application engineers, cloud security, and governance stakeholders to embed security into AI delivery.</li><li>
Contribute to the evolution of enterprise AI security standards, patterns, and reference architectures.</li><li>
Support incident response, threat modeling, and remediation activities related to AI systems.</li></ul><p><b>
Required Qualifications</b><br>
The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.</p><ul><li>
Bachelor&rsquo;s degree or equivalent education, training, and work-related experience.</li><li>
Minimum of 7 years of experience in security engineering or related cybersecurity roles.</li><li>
Deep specialized knowledge in cybersecurity principles, theories, and concepts.</li><li>
Proven experience in software development lifecycle security practices.</li><li>
Deep knowledge of threat modeling, security testing, and penetration testing.</li><li>
Experience implementing and managing complex information security technologies.</li></ul><p><b>
Technical Skills &amp; Emerging Skills Experience</b></p><ul><li>
Strong hands-on experience with Azure and/or AWS</li><li>
Infrastructure as Code experience with Terraform and CloudFormation.</li><li>
Experience building and managing CI/CD pipelines (GitLab).</li><li>
Experience implementing or operating cloud security tooling (e.g., Microsoft Purview, Sentinel, Wiz or equivalent).</li><li>
Experience securing AI/ML or Generative AI systems in production environments.</li><li>
Familiarity with AI-specific security controls, such as:<ul><li>
Prompt injection mitigation</li><li>
Content safety / moderation controls</li><li>
Model access and usage restrictions</li><li>
Secure data handling for AI pipelines</li></ul></li><li>
Exposure to Azure and Azure-hosted AI services.</li><li>
Experience working in regulated environments with strong risk and governance requirements.</li></ul><p><b>
General Description of Available Benefits for Eligible Employees of Truist Financial Corporation: </b>All regular teammates (not temporary or contingent workers) working 20 hours or more per week are eligible for benefits, though eligibility for specific benefits may be determined by the division of Truist offering the position. Truist offers medical, dental, vision, life insurance, disability, accidental death and dismemberment, tax-preferred savings accounts, and a 401k plan to teammates. Teammates also receive no less than 10 days of vacation (prorated based on date of hire and by full-time or part-time status) during their first year of employment, along with 10 sick days (also prorated), and paid holidays. For more details on Truist&rsquo;s generous benefit plans, please visit our Benefits site. Depending on the position and division, this job may also be eligible for Truist&rsquo;s defined benefit pension plan, restricted stock units, and/or a deferred compensation plan. As you advance through the hiring process, you will also learn more about the specific benefits available for any non-temporary position for which you apply, based on full-time or part-time status, position, and division of work.</p><p><b><i>
Truist is an Equal Opportunity Employer that does not discriminate on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status, or other classification protected by law. Truist is a Drug Free Workplace.</i></b></p><p>
EEO is the Law E-Verify IER Right to Work</p></div>
</div><div></div><div><div><p>Type</p><div><p>
Full-time</p></div></div></div></div>

Cybersecurity Senior Engineer (AI Cloud Security)

Apple

<p>Do you want first crack at new Apple Pay products? Come help them be more secure by breaking them first!<br>
<br>
Join our Apple Pay Security Engineering team and help us deliver the safest and best user-experience. We work on Payments, Transit, Access, &amp; Identity, across hardware, software, and server. If you're passionate about digital security and customer safety, we may have the job for you.<br>
<br>
<b>Description</b><br>
<br>
You're a security engineer at heart: a pentester who breaks hardware, software, and services to find what others miss. You use AI to move faster and improve the tooling as you go: not shipping product features but building the Skills, Agents, and workflows that make our security testing sharper. Above all, you can disagree with the AI, prove it wrong, and make it better instead of rubber-stamping its results.&quot;,&quot;responsibilities&quot;:&quot;Develop AI workflows to perform security review and security testing<br>
<br>
Develop Skills and Agents that instill security best practices into every phase of the SDLC: design, implementation, review, build/CI-CD, and post-launch<br>
<br>
Threat model development and secure design assessment of hardware and software<br>
<br>
Hands-on testing of hardware and software<br>
<br>
Validate and challenge AI findings, not just consume them<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Superior problem solving and debugging skills<br>
<br>
Understanding of the use of various cryptographic algorithms (RSA, AES, SHA, etc.)<br>
<br>
Able to clearly communicate across many teams (Can you nicely tell the developer that they have a bug?)<br>
<br>
Ability to propose new designs and architectural improvements (Can you redesign what you just broke?)<br>
<br>
Experience either shipping software or integrating security into every stage of the software lifecycle.<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
Drive and agency: You know how to use tools to learn new areas, experiment, and develop security issue discovery capabilities. You&rsquo;re curious and interested in learning new areas. You have a sense of ownership and pride in improving the environment.<br>
<br>
Security engineering foundation: You&rsquo;ve threat modeled hardware and/or software designs, determining where attacks would come from and what protections exist in a design. You&rsquo;ve performed hands-on security testing (pentesting, negative testing, or equivalent). You&rsquo;re skilled at security code reviews.<br>
<br>
AI/agentic fluency: You have hands-on experience using agentic/LLM-based coding tools. You&rsquo;re able to build and refine Skills, Agents and AI workflows, not just operate them. You&rsquo;re able to independently verify or refute a finding rather than accept it at face value<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.<br>
<br>
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Security Engineer - Apple Pay

VaporVM

<div><div><div><b>Date Posted:</b></div>
11 June, 2026</div>
<div><div><b>Industry:</b></div>
IT Services and IT Consulting</div>
<div><div><b>Location:</b></div>
VaporVM</div></div>
<br><div><h2 class="jobSectionHeader"><b>Job Description:</b></h2>
<div><h1 class="jobSectionHeader"><b>Senior HPC / Infrastructure Engineer</b></h1>
<p><b>
Location:</b> Riyadh, Saudi Arabia</p>
<p><b>
Employment Type:</b> Full-Time</p>
<p><b>
Experience:</b> 10+ Years (Hands-On)</p>
<h2 class="jobSectionHeader"><b>
Position Overview</b></h2>
<p>
We are seeking a highly experienced <b>Senior HPC / Infrastructure Engineer</b> with proven expertise in designing, deploying, and operating enterprise-scale High-Performance Computing (HPC) and AI infrastructure environments. This role is ideal for a hands-on technical leader who has built and managed production-grade HPC platforms, GPU clusters, Kubernetes ecosystems, and AI infrastructure from the ground up.</p>
<p>
The successful candidate will play a critical role in architecting, optimizing, and maintaining mission-critical compute environments that support advanced AI/ML, data science, and high-performance workloads.</p>
<h2 class="jobSectionHeader"><b>
Required Certifications</b></h2>
<ul><li><b>RHCE &ndash; Red Hat Certified Engineer (Active)</b></li>
<li><b>CKA &ndash; Certified Kubernetes Administrator (Active)</b></li>
</ul><h2 class="jobSectionHeader"><b>Core Technical Expertise</b></h2>
<h3 class="jobSectionHeader"><b>HPC &amp; NVIDIA AI Ecosystem</b></h3>
<ul><li>NVIDIA Base Command Manager (BCM)</li>
<li>NVIDIA AI Enterprise</li>
<li>NVIDIA GPU Operator &amp; Network Operator</li>
<li>NVIDIA NIM Inference Services</li>
<li>NVIDIA AI Blueprints</li>
<li>CUDA, GPU Drivers, and Performance Optimization</li>
</ul><h3 class="jobSectionHeader"><b>Compute &amp; Container Platforms</b></h3>
<ul><li>Kubernetes (Architecture, Operations &amp; Scaling)</li>
<li>Slurm Workload Manager</li>
<li>Distributed Computing Environments</li>
</ul><h3 class="jobSectionHeader"><b>Operating Systems</b></h3>
<ul><li>Red Hat Enterprise Linux (RHEL)</li>
<li>Ubuntu LTS (Canonical)</li>
</ul><h3 class="jobSectionHeader"><b>Automation &amp; DevOps</b></h3>
<ul><li>CI/CD Pipeline Design &amp; Implementation</li>
<li>Infrastructure Automation</li>
<li>Platform Lifecycle Management</li>
<li>Configuration Management &amp; Orchestration</li>
</ul><h2 class="jobSectionHeader"><b>Key Responsibilities</b></h2>
<ul><li>Design, deploy, and operate large-scale HPC and AI infrastructure environments from bare metal through workload orchestration.</li>
<li>Architect and manage NVIDIA GPU platforms, including BCM, AI Enterprise, GPU Operator, and AI service enablement.</li>
<li>Configure, optimize, and maintain Slurm scheduling environments for high-throughput and GPU-intensive workloads.</li>
<li>Design and operate highly available Kubernetes clusters supporting AI/ML, analytics, and containerized workloads.</li>
<li>Enable and support NVIDIA NIM services and AI Blueprint deployments for enterprise AI initiatives.</li>
<li>Administer and optimize RHEL and Ubuntu environments, ensuring stability, security, and performance.</li>
<li>Develop and maintain infrastructure automation frameworks and CI/CD pipelines for platform and application deployment.</li>
<li>Optimize performance across compute, GPU, storage, networking, and cluster resources.</li>
<li>Implement monitoring, observability, alerting, capacity planning, and operational best practices.</li>
<li>Enforce security, patch management, access controls, and compliance standards across the infrastructure stack.</li>
<li>Lead troubleshooting, root cause analysis, and resolution of complex infrastructure and platform issues.</li>
</ul><h2 class="jobSectionHeader"><b>Candidate Profile</b></h2>
<ul><li>10+ years of hands-on experience in HPC, Linux infrastructure, and enterprise platform engineering.</li>
<li>Proven track record of building and operating production-scale HPC, GPU, or AI infrastructure environments.</li>
<li>Deep expertise in Kubernetes, Slurm, Linux administration, and NVIDIA AI technologies.</li>
<li>Strong understanding of distributed systems, workload scheduling, cluster management, and performance optimization.</li>
<li>Experience supporting AI/ML, data science, and high-performance computing workloads at scale.</li>
<li>Strong analytical, troubleshooting, and problem-solving skills.</li>
<li>Ability to work across infrastructure, platform, automation, and AI enablement domains.</li>
<li>Demonstrated ownership mindset with a history of delivering reliable, scalable, and high-performing solutions.</li></ul></div></div><p></p>

Senior Infrastructure / HPC

FTI Defense

<div>Overview:
<div>
FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.</div><div></div><div><br>
FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.</div>
Responsibilities:
<ul><li>Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.</li><li>
Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.</li><li>
Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).</li><li>
Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).</li><li>
Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.</li><li>
Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).</li><li>
Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.</li><li>
Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.</li><li>
Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.</li><li>
Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.</li></ul>
Education/Qualifications:
<div><b>
Minimum Requirements:</b></div><ul><li><b>
Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.</b></li><li>
6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.</li><li>
Minimum of 3 years' professional experience within the <b>Department of Defense/Department of War (DoD/DoW)</b> AI assurance, security, and deployment environments.</li><li>
Strong Python development skills with hands-on experience building AI/ML solutions.</li><li>
Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.</li><li>
Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.</li><li>
Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).</li><li>
Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.</li><li>
Professional experience integrating AI capabilities into production systems or mission applications.</li></ul><div>
 <b>Preferred Qualifications:</b></div><ul><li>
Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.</li><li>
Understanding of prompt engineering, retrieval quality, and grounding methods.</li><li>
Exposure to GPU-based or edge inference environments.</li><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Data Science, or a related technical field.</li><li>
Active Secret clearance preferred; ability to obtain one is <b>required</b>.</li></ul><div></div><div><br>
#LI-KM1</div><div>
#LI-Remote</div></div>

AI/ML Engineer

MANTECH

<div><p>MANTECH seeks a motivated, career, and customer-oriented <b>AI Engineer</b> for a new initiative. This effort supports the rapid design, deployment, operation, and sustainment of enterprise-scale AI, data, and mission platform capabilities across a cloud, edge, and classified operational environment.</p><p>
The <b>AI Engineer</b> supports the development and operationalization of advanced AI and agentic AI systems in production mission environments. You will accelerate operational AI adoption through a modern Hub-and-Spoke architecture, supporting mission applications and enterprise AI governance.</p><p></p><p><b>
Responsibilities include but are not limited to:</b></p><ul><li>
Design, develop, and operationalize full-lifecycle AI/ML operations (MLOps/LLMOps).</li><li>
Implement and deploy Retrieval-Augmented Generation (RAG) architectures in production.</li><li>
Build and maintain scalable AI orchestration frameworks and production-ready AI systems.</li><li>
Manage and optimize Kubernetes-based AI deployments, focusing on GPU inference optimization.</li><li>
Conduct core Python development for AI systems and integrate OpenAI-compatible APIs into mission solutions.</li><li>
Operationalize AI agents using advanced frameworks like LangGraph or Semantic Kernel.</li></ul><p></p><p><b>
Minimum Qualifications:</b></p><ul><li>
Must possess 7 or more years of experience in AI/ML production engineering, development, or related roles. Relevant additional experience will be considered in lieu of degree.</li><li>
Proven proficiency in Python development and experience with AI/ML libraries like TensorFlow or PyTorch.</li><li>
In-depth knowledge of MLOps/LLMOps principles and full machine learning lifecycle management.</li><li>
Experience with Kubernetes-based AI deployments and GPU optimization techniques.</li><li>
Proven experience designing, building, securing or monitoring scalable solutions within the Microsoft Azure ecosystem (e.g., Azure OpenAI, Azure Synapse, Databricks, or Azure Security Center).</li></ul><p></p><p><b>
Preferred Qualifications:</b></p><ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering or a related field.</li><li>
Experience with LangGraph, Semantic Kernel, and agentic AI systems.</li><li>
Familiarity with Ray, NVIDIA GPU ecosystems, or Vector databases.</li><li>
Advanced degree (Master's or PhD) in a technical field.</li></ul><p></p><p><b>
Clearance Requirements:</b></p><ul><li>
TS/SCI with the ability to obtain and maintain a polygraph</li></ul><p></p><p><b>
Physical Requirements:</b></p><ul><li>
The person in this position must be able to remain in a stationary position 50% of the time.</li><li>
Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.</li><li>
Constantly operates a computer and other office productivity machinery.</li></ul></div><p></p>

AI Engineer

TAWANTECH

<div><p><b>Job Summary</b></p><p>
We are seeking an AI Software Engineer with hands-on experience in Large Language Models (LLMs) and Generative AI technologies to develop intelligent solutions that enhance customer experience, operational efficiency, and knowledge management within the banking sector.</p><p></p><p><b>
Key Responsibilities</b></p><ul><li>Design, develop, and deploy AI-powered applications leveraging LLMs and Generative AI.</li><li>Build Retrieval-Augmented Generation (RAG) solutions using enterprise banking data.</li><li>Develop intelligent assistants, chatbots, and knowledge management solutions.</li><li>Integrate AI services with banking applications and APIs.</li><li>Fine-tune, evaluate, and optimize LLM performance.</li><li>Ensure compliance with banking security, governance, and regulatory requirements.</li><li>Collaborate with business, data, and technology teams to deliver AI-driven solutions.</li></ul><b><br>
Requirements</b><ul><li><br>
4+ years of software engineering experience.</li><li>Strong Python programming skills.</li><li>Experience with LLMs, Generative AI, and Prompt Engineering.</li><li>Experience with LangChain, LlamaIndex, Vector Databases, and RAG architectures.</li><li>Familiarity with machine learning frameworks and AI deployment practices.</li><li>Experience with cloud platforms (AWS, Azure, GCP) is preferred.</li></ul><p></p><p><b>
Preferred Qualifications</b></p><ul><li>Banking or Financial Services experience.</li><li>Experience developing AI copilots or customer-facing AI solutions.</li><li>Knowledge of AI governance and responsible AI practices.</li></ul></div>

AI Software Engineer / LLM Engineer

Octo Outsourcing

<p>AWS Native Full-Stack / AI Platform Developer</p><p><b>Location:</b> Pakistan / Remote<br/><b>Employment Type:</b> Full-time<br/><b>Company:</b> Octo Apps / OctoApps.ai<br/><b>Department:</b> Cloud, AI Engineering, DevOps &amp; Platform Operations<br/><b>Reports To:</b> Chief Architect / Principal AI Developer</p><p>About the Role</p><p>We are looking for a strong <b>all-rounder AWS Native Developer</b> who can take full ownership of development, testing, security, deployment, troubleshooting, and platform operations for the <b>Octo Apps platform on AWS</b>.</p><p>This role is not limited to coding only. The ideal candidate must understand how application development, AWS infrastructure, DevOps, testing, monitoring, security, APIs, and AI features work together to deliver a stable, scalable, and production-ready platform. The candidate will be responsible for helping us complete, stabilize, secure, and operate Octo Apps with a target of <b>99.99% availability</b>.</p><p>You will work directly with the Chief Architect to build and manage <b>Octo Apps AI</b>, including AI-powered developer productivity tools, automation workflows, RAG-based knowledge systems, phone-system integrations, messaging APIs, and cloud-native application services.</p><p>Key Responsibilities</p><ul><li>Take end-to-end ownership of assigned Octo Apps modules, including development, testing, deployment, monitoring, troubleshooting, and support.</li><li>Develop, improve, and stabilize AWS-native applications, backend services, APIs, automation workflows, and AI-powered features.</li><li>Manage AWS infrastructure and cloud services such as <b>Lambda, API Gateway, S3, CloudFront, ECS/Fargate, EC2, RDS, DynamoDB, IAM, CloudWatch, Route 53, Secrets Manager, Bedrock, and related services</b>.</li><li>Ensure platform reliability, uptime, performance, scalability, and production readiness with a target of <b>99.99% availability</b>.</li><li>Build and maintain monitoring, alerting, logging, backup, recovery, and incident-response processes.</li><li>Perform application testing, integration testing, API testing, regression testing, security testing, and production validation before releases.</li><li>Identify, troubleshoot, and resolve issues across application code, APIs, database, AWS infrastructure, IAM permissions, environment variables, DNS, SSL, networking, and deployment pipelines.</li><li>Implement security best practices, including IAM least privilege, secrets management, secure API authentication, encrypted storage, secure deployments, and access control.</li><li>Work on AI application features such as prompt workflows, RAG pipelines, vector search, document ingestion, AI agents, automation tools, and AI API integrations.</li><li>Integrate third-party APIs including <b>Meta, WhatsApp, Messenger, Telnyx, Twilio, SendGrid, Stripe, AI APIs, CRM tools, and other business systems</b>.</li><li>Build and maintain CI/CD pipelines using GitHub Actions or similar tools.</li><li>Document architecture, deployment steps, troubleshooting guides, test cases, release procedures, and operational runbooks.</li><li>Proactively recommend improvements for performance, security, reliability, automation, and cost optimization.</li><li>Provide regular status updates, identify risks early, and take ownership until issues are fully resolved.</li></ul><p>Required Skills</p><ul><li>Strong hands-on experience with <b>AWS cloud services</b> and cloud-native application development.</li><li>Good understanding of <b>infrastructure, networking, IAM, serverless, containers, APIs, monitoring, logging, and cloud security</b>.</li><li>Backend development experience using <b>Node.js, Python, FastAPI, Express.js, NestJS, or similar technologies</b>.</li><li>Frontend understanding with <b>React, Next.js, or modern web application frameworks</b>.</li><li>Experience building, consuming, securing, and debugging <b>REST APIs</b>.</li><li>Experience with databases such as <b>PostgreSQL, MySQL, MongoDB, DynamoDB, or RDS</b>.</li><li>Understanding of <b>AI APIs</b>, including OpenAI, Claude, AWS Bedrock, or similar platforms.</li><li>Familiarity with <b>RAG, embeddings, vector databases, prompt engineering, AI workflows, or AI agents</b>.</li><li>Experience with <b>Git, GitHub, CI/CD, environment management, and production deployments</b>.</li><li>Strong testing mindset, including unit testing, integration testing, API testing, regression testing, and release validation.</li><li>Strong security mindset, including authentication, authorization, secrets handling, secure APIs, and access control.</li><li>Ability to debug independently and take ownership of issues until resolution.</li></ul><p>Preferred Skills</p><ul><li>Experience with <b>AWS Bedrock, SageMaker, Lambda, ECS/Fargate, DynamoDB, RDS, S3, CloudFront, CloudWatch, Route 53, and Secrets Manager</b>.</li><li>Experience with vector databases such as <b>Pinecone, Weaviate, Chroma, OpenSearch, pgvector, or similar</b>.</li><li>Experience with <b>Docker, Terraform, CloudFormation, AWS CDK, or infrastructure-as-code</b>.</li><li>Experience with authentication systems such as <b>OAuth, JWT, Cognito, Clerk, Auth0, or custom auth systems</b>.</li><li>Experience integrating communication APIs such as <b>Meta, WhatsApp, Messenger, Telnyx, Twilio, SendGrid, or similar</b>.</li><li>Experience supporting production SaaS platforms, multi-tenant applications, developer tools, contact-center systems, or workflow automation products.</li><li>Basic knowledge of disaster recovery, high availability, load balancing, failover, backup strategy, and incident management.</li><li>AWS certification is a plus but not mandatory.</li></ul><p>Ideal Candidate Profile</p><p>We need someone who can operate like a <b>developer, DevOps engineer, tester, security-minded engineer, and production support owner</b>. The ideal person should not wait for step-by-step instructions. They should be able to investigate problems, review logs, test fixes, improve architecture, secure the platform, document solutions, and make sure the system remains stable and available.</p><p>This person must be comfortable working in a fast-moving startup environment where ownership, accountability, and problem-solving are more important than narrow job boundaries.</p><p>Key Projects You May Work On</p><ul><li>Octo Apps AI developer productivity platform.</li><li>AI-powered automation and workflow tools.</li><li>RAG-based document and knowledge retrieval systems.</li><li>Phone system and messaging integrations with WhatsApp, Messenger, Telnyx, Twilio, and other APIs.</li><li>AWS-native backend services, APIs, infrastructure, and deployment automation.</li><li>Security, monitoring, logging, testing, backup, and high-availability improvements.</li><li>Internal admin dashboards, API routing, AI workflow orchestration, and production support tools.</li></ul><p>Qualifications</p><ul><li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, IT, or equivalent practical experience.</li><li>4+ years of software development, cloud engineering, DevOps, or platform engineering experience.</li><li>2+ years of hands-on AWS experience preferred.</li><li>Experience with AI application development, AI APIs, or automation platforms preferred.</li><li>Strong communication, ownership, documentation, and troubleshooting skills.</li></ul><p>Compensation</p><p>Market-competitive salary based on experience, ownership level, and technical capability. Performance-based growth opportunities may be available as the platform scales.</p><p>How to Apply</p><p>Please send your resume, GitHub/profile links, AWS project experience, production support experience, and examples of any AI/API/cloud projects you have worked on.</p><p>Pay: Rs175,000.00 - Rs250,000.00 per month</p><p>Work Location: Remote</p>

AWS Full Stack Developer

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