ai research engineer

Speechify

<div>The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify's text-to-speech products to turn whatever they're reading &ndash; PDFs, books, Google Docs, news articles, websites &ndash; into audio, so they can read faster, read more, and remember more. Speechify's text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.
Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting &ndash; Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You'll Do
<ul>
<li>Be scrappy to find new sources of audio data and bring it into our ingestion pipeline</li>
<li>Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.</li>
<li>Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.</li>
<li>Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team's dataset roadmap to power Speechify's next-generation consumer and enterprise products.</li>
</ul>
An Ideal Candidate Should Have
<ul>
<li>BS/MS/PhD in Computer Science or a related field.</li>
<li>5+ years of industry experience in software development.</li>
<li>Proficiency with bash/Python scripting in Linux environments</li>
<li>Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)</li>
<li>Experience with web crawlers, large-scale data processing workflows is a plus</li>
<li>Ability to handle multiple tasks and adapt to changing priorities.</li>
<li>Strong communication skills, both written and verbal.</li>
</ul>
What we offer
<ul>
<li>A fast-growing environment where you can help shape the company and product.</li>
<li>An entrepreneurial-minded team that supports risk, intuition, and hustle.</li>
<li>A hands-off management approach so you can focus and do your best work.</li>
<li>An opportunity to make a big impact in a transformative industry.</li>
<li>Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.</li>
<li>Opportunity to work on a life-changing product that millions of people use.</li>
<li>Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.</li>
<li>Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.</li>
</ul>
Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience

Think you're a good fit for this job?

Tell us more about yourself and why you're interested in the role when you apply.
 
And don't forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit?

Refer them!

Speechify is committed to a diverse and inclusive workplace.

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.</div>

Software Engineer, Data Infrastructure & Acquisition - Mountain View, CA, USA

Tesla

<div>What to Expect<div>
At Tesla AI, we are solving real-world autonomy at a scale that does not exist anywhere else. We are building the brains for millions of robots and to achieve this, we train frontier-scale foundation models on the world&rsquo;s richest, most diverse dataset of multimodal telemetry, vision, language, and robotic action. You will have access to unparalleled resources that set us apart from other companies in the AI industry. You will work with one of the richest real-world driving, robotics and human-interaction datasets available, spanning vision, language, action, and on-robot telemetry providing a unique environment to study how capability transfers from large teacher models into compact students that must run under strict latency, power, and reliability constraints. Tesla also offers one of the highest GPU resources per engineer in the industry, giving you the computational budget to train frontier-scale teachers, generate high-quality distillation corpora at volume, and iterate on student architectures far beyond typical research environments.
These resources enable you to run distillation experiments across language, multimodal, and policy models at a fidelity and scale unmatched elsewhere, and to close the loop by deploying distilled models onto FSD / Optimus in the real world. 
</div> 
What You'll Do<div><ul><li>
Design and execute state-of-the-art distillation pipelines that transfer complex reasoning, vision-language understanding, and action policies from massive teacher models to ultra-efficient student models for FSD (Full Self-Driving), Optimus, and Digital Optimus</li><li>
Develop and iterate on advanced distillation methodologies, including logit-level, sequence-level, and trajectory-level distillation. You will pioneer novel recipes combining synthetic data generation, soft-label training, supervised fine-tuning (SFT), and Reinforcement Learning (RL)</li><li>
Conduct experiments to uncover the scaling behaviors of distillation: teacher size, student capacity, student architecture design, data mixture, compute allocation, and how each factor affects capability retention, latency, and on-robot performance</li><li>
Build and maintain infrastructure for efficient large-scale teacher inference, distillation data curation, and distributed student training, resolving compute and memory bottlenecks end-to-end</li><li>
Evaluate distilled models against teacher fidelity and product metrics like task success, robustness, and real-world behaviors and close gaps where students diverge from teachers</li><li>
Work closely with cross-functional teams to ship distilled models to production, meeting stringent performance, safety, and reliability standards</li><li>
Contribute tools and frameworks that make distillation reproducible, measurable, and reusable across Tesla AI model families</li></ul></div> 

What You'll Bring<div><ul><li>
Deep, proven expertise in deep learning fundamentals, particularly in training, compressing, or distilling large-scale language, vision, or multimodal models</li><li>
Strong grasp of teacher&ndash;student interaction, synthetic data, and the tradeoffs between capability, latency, and compute</li><li>
In-depth knowledge of loss design (e.g., KL / soft-target objectives), and modern neural architectures (mixture of experts, hybrid attention, and beyond)</li><li>
Hands-on familiarity with post-training methods such as distillation, supervised fine-tuning, and policy optimization / RL</li><li>
Strong expertise in distributed computing and large-scale training or inference pipelines</li><li>
Proficiency in Python and a deep understanding of software engineering best practices</li><li>
Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX</li><li>
Demonstrated ability to work collaboratively in a cross-functional team environment</li><li>
Strong problem-solving skills and the ability to troubleshoot complex system-level issues across data, training, and deployment</li></ul></div> 

Compensation and Benefits<div>
Benefits</div><div>
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
<ul><li>Medical plans &gt; plan options with $0 payroll deduction</li>
<li>Family-building, fertility, adoption and surrogacy benefits</li>
<li>Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution</li>
<li>Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA</li>
<li>Healthcare and Dependent Care Flexible Spending Accounts (FSA)</li>
<li>401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits</li>
<li>Company paid Basic Life, AD&amp;D</li><li>
Short-term and long-term disability insurance (90 day waiting period)</li>
<li>Employee Assistance Program</li>
<li>Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays</li>
<li>Back-up childcare and parenting support resources</li>
<li>Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft &amp; legal services, and pet insurance</li>
<li>Weight Loss and Tobacco Cessation Programs</li>
<li>Tesla Babies program</li>
<li>Commuter benefits</li>
<li>Employee discounts and perks program</li>
</ul></div><div>Expected Compensation</div><div>
$124,000 - $558,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.</div> 
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws. 
 
Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.</div>

AI Engineer, Model Distillation, Tesla AI

Smvsoft LLC

Founding Engineer - Applied AI San francisco, CA (Full time)- In-Office$180k-$230k per annumNO C2CAbout the RoleHiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.Key Responsibilities<ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul>RequirementsMust-Have<ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul>Nice-to-Have<ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul>Pay: $180,000.00 - $230,000.00 per yearWork Location: In person

Founding Engineer - Applied AI

Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</div><div><h2 class="jobSectionHeader">
About the role</h2>

The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse &mdash; keeping fraud losses, dispute rates, and network monitoring exposure in check while preserving a smooth experience for legitimate customers. As a software engineer on this team, you will build the systems that make risk decisions in real time, manage the dispute and chargeback lifecycle, and detect monetization abuse across subscriptions, in-app purchases, and promotions. The ideal candidate can see things from attackers' perspectives, anticipate their responses to countermeasures, and never loses sight of the fact that a false positive here is a paying customer.

Payments fraud is more externally coupled than most trust and safety work &mdash; you'll collaborate closely with finance, support, and legal teams internally, and with payment processors and platform partners externally.
<h2 class="jobSectionHeader">
Responsibilities:</h2>
<ul><li>Design and build real-time risk decisioning that scores transactions at authorization time, balancing fraud loss, approval rates, and latency constraints</li>
<li>Build tooling and automation for the dispute and chargeback lifecycle, from review queues to evidence collection and loss reporting</li>
<li>Engineer fraud signals at scale &mdash; device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage &mdash; and detect monetization abuse across subscriptions, trials, promotions, and in-app purchases</li>
<li>Own a portfolio of metrics &mdash; loss rate, dispute rate, authorization approval impact, and false-positive rate &mdash; rather than optimizing any single number</li>
<li>Lead investigations into emerging fraud patterns, building multi-layered defenses designed for attacker adaptation rather than point-in-time rules</li>
<li>Work cross-functionally with finance, support, legal, and data science, and with external payment processors and platform partners</li>
</ul><h2 class="jobSectionHeader">Minimum Qualifications:</h2>
<ul><li>Proficiency in Python, SQL, and data analysis tools</li>
<li>Experience building or operating fraud, risk, or abuse detection systems in production</li>
<li>Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders</li>
</ul><h2 class="jobSectionHeader">Preferred Qualifications:</h2>
<ul><li>8+ years of industry software engineering experience, with a focus on payments fraud or risk</li>
<li>Fluency with payments rails: card networks, payment service providers (e.g., Stripe, Adyen), in-app purchase platforms (Apple, Google), refund flows, and the chargeback and dispute lifecycle</li>
<li>Direct experience combating fraud typologies such as card testing, stolen-card monetization, refund and chargeback abuse, subscription and trial abuse, promotional abuse, and friendly fraud</li>
<li>Understanding of fraud loss accounting &mdash; fraud loss vs. dispute fees vs. card network monitoring programs (e.g., VDMP, i VFMP, Mastercard ECP) &mdash; and why chargeback rate thresholds carry existential stakes</li>
<li>Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows</li>
<li>Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team</li>
</ul></div><div><div><div><div>
The annual compensation range for this role is listed below.

For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</div></div>
Annual Salary:
$320,000 - $485,000 USD</div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 
 
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.
<h2 class="jobSectionHeader">
How we're different</h2>

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
<h2 class="jobSectionHeader">
Come work with us!</h2>

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.</div></div>

Staff+ Software Engineer, Financial Fraud

Developers Den LLC

Company Description We're an AI Product engineering team that builds AI products, Voice AI systems, and SaaS platforms for startups.We're looking for an SEO Content Writer who understands that a blog post isn't done because it's well written; it's done when it ranks, earns a reader, and builds the funnel. You'll own the website's organic growth and write content that positions Developers Den as the team that startup founders trust to engineer their products.Role Description This is a writing role first, an SEO role second, and a marketing role at its core. You'll research and write on technical topics, AI agents, SaaS architecture, automation, product engineering credibly enough that CTOs and founders trust what they're reading. You understand search intent, on-page SEO, and how content moves someone from a stranger to a lead, not just whether a sentence reads well.What You Will OwnWebsite Content<ul><li>Service pages, landing pages, homepage copy that converts organic visitors</li><li>Blog posts and long-form guides that rank for our target keywords</li><li>Case studies from an intake conversation with our team to a published, sales-ready story</li></ul>SEO Execution<ul><li>Conduct keyword research, search intent mapping, and topic clustering to support website growth, content marketing initiatives, and core service pages.</li><li>Optimize content for traditional search (SEO) as well as AI-powered discovery through Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO), ensuring content is structured for search engines and AI assistants.</li><li>On-page SEO: meta titles, header structure, internal linking, content structure</li><li>Monthly reporting on organic traffic, rankings, and content performance using Google Search Console and related SEO tools.</li></ul>Content Quality and Consistency<ul><li>Maintain Developers Den's voice across every page and post: clear, confident, no fluff, no generic AI agency language</li><li>Edit and tighten drafts so every piece earns its length</li><li>Support content repurposing efforts by adapting website content into additional marketing assets where required.</li></ul>Requirements<ul><li>1+ years writing SEO content, ideally for a tech, Startups, or B2B audience</li><li>Strong grasp of on-page SEO fundamentals, keyword placement, search intent, meta structure, internal linking</li><li>Comfortable using AI tools to speed up research and drafting, but the judgment, structure, and final voice are yours, not the tool's</li><li>Comfortable publishing and formatting content in WordPress.</li><li>Understanding of funnel stages and how content format should match buyer intent</li></ul>To Apply To apply, fill out the application form: https://docs.google.com/forms/d/1msCeJgweemUdXI_4KYP7Y8wkaqVjHUQcG0gbE5ycNMg/viewform?edit_requested=trueUpload your resume along with 2&ndash;3 writing samples. If you have content that ranked on search engines or drove measurable traffic, include it. We value impact as much as writing quality.Pay: Rs21,555.51 - Rs78,022.10 per monthWork Location: In person

SEO Content Writer

BV Teck

<div>Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. 
 
Job Title: AI Risk Engineer 
Location: 100% Remote (Continental United States) 
Position Type: Full-time, Direct W2 
Salary Range: $100,000 to $150,000 per annnum 
Experience: 6+ years 
 
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. 
Job Summary: 
We are seeking an AI Risk Engineer to design and implement security controls for AI and machine learning systems. The ideal candidate will have expertise in AI security, threat modeling, LLM protection, cloud security, and incident response, with experience securing AI-powered applications and infrastructure.
Key Responsibilities:<ul><li>
Design and implement security controls for AI and LLM-based applications.</li><li>
Build threat models and mitigate risks such as prompt injection, model abuse, and data exfiltration.</li><li>
Implement guardrails, monitoring, logging, and incident response for AI systems.</li><li>
Secure AI training pipelines, APIs, and multi-tenant environments.</li><li>
Collaborate with security, privacy, and compliance teams to strengthen AI security posture.</li><li>
Conduct AI security assessments and drive remediation of identified risks.</li></ul>
Required Qualifications:<ul><li>
6+ years of security engineering experience, including AI or ML systems.</li><li>
Strong knowledge of LLM security, application security, cloud security, and threat modeling.</li><li>
Experience with AI security controls, adversarial ML, prompt injection, and Python.</li></ul>
Preferred Qualifications:<ul><li>
Experience with AI red-teaming, privacy-preserving ML, or AI security research.</li><li>
Exposure to regulated industries or open-source AI security tools.</li></ul>
How to Apply 
Would you like to know more about this opportunity? For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com. 
 
Bright Vision Technologies is an Equal Opportunity Employer.
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
wmYoG00cNg</div>

Risk Engineer - AI

Infomineo

<div>
 
 
 About us
 
 
 
 Infomineo is a pioneering global AI-enhanced research company that transforms how businesses access, analyze, and act on critical intelligence. We&rsquo;ve evolved from traditional business research outsourcing to become the strategic partner that combines cutting-edge artificial intelligence with deep human expertise. We offer 3 services to our global clients (leading consulting companies, Fortune 500 companies, and government entities): AI and Data Advisory, Next-Gen Insights and Resource Scaling. This is made possible by relying on 3 pillars of excellence:
 
 
 
 
 <ol>
 <li>
 350+ industry experts spread across 5 offices (Cairo, Casablanca, Mexico City, Dubai, Barcelona).
 </li>
 <li>
 Our proprietary AI orchestrator.
 </li>
 <li>
 Extensive knowledge assets combining 500,000+ delivered case studies and database subscriptions.
 </li>
 </ol>
 
 
 
 
 Ready to kick start your career with us?
 
 
 
 Why Infomineo? Here&rsquo;s what sets us apart:
 
 
 <ul>
 <li>
 
 Shape the Future of Business Insights:
 
 You will be at the forefront, leading the design and implementation of AI-driven solutions that automate tasks and drive efficiency across our entire service spectrum (Business Research, Content, Design, and Data Analytics).
 </li>
 <li>
 
 Work with Global Leaders:
 
 Our clients are industry leaders &mdash; Fortune 500s, top consultancies, governments, and NGOs. You will take ownership of delivering technical solutions that directly support their success.
 </li>
 <li>
 
 Lead in AI &amp; Technology:
 
 We foster continuous learning and technical excellence. You will stay ahead of the latest advancements in AI and software engineering, and actively drive innovation across the team.
 </li>
 <li>
 
 Thrive in a Collaborative Culture:
 
 We value intellectual curiosity, leadership, and a can-do attitude. You will be encouraged to mentor others, contribute strategic ideas, and make a lasting impact on the company&rsquo;s growth.
 </li>
 </ul>
 
 
 
 
 
 About this role:
 
 
 
 We are seeking an experienced and technically strong individual to join us as
 
 Senior AI Software Engineer.
 
 In this role, you will take ownership of designing, developing, and deploying AI-powered data products and analytical applications that serve our internal teams and global clients. You will lead data science and AI initiatives, define best practices for applied AI and analytical solution development, and collaborate closely with engineering, product, and business stakeholders. While the role is primarily data science and AI-focused, you will also leverage your full-stack development background to build production-ready applications, integrate AI capabilities, and support cloud-based deployment.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Data Science, AI &amp; Applied R&amp;D:
 
 
 <ul>
 <li>
 Lead the design and development of AI-powered analytical solutions, data products, and intelligent applications that solve complex business problems.
 </li>
 <li>
 Translate business and client requirements into data science approaches, AI workflows, and scalable technical solutions.
 </li>
 <li>
 Design, prototype, and productionize machine learning, LLM, and generative AI solutions with a focus on business value, reliability, and usability.
 </li>
 <li>
 Own the architecture of Retrieval-Augmented Generation (RAG) pipelines, including document processing, vectorization, semantic search, evaluation, and query optimization for enterprise use cases.
 </li>
 <li>
 Design and implement complex AI-powered features by integrating LLM APIs and services using frameworks such as LangChain or equivalent, with a focus on reliability, accuracy, and performance in production.
 </li>
 <li>
 Design, implement, and maintain Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and data sources, enabling context-aware and extensible AI solutions.
 </li>
 <li>
 Develop evaluation frameworks, monitoring approaches, and observability practices for LLM-powered systems to ensure quality, transparency, and continuous improvement.
 </li>
 <li>
 Apply advanced prompt engineering, embedding strategies, and vector database management techniques to improve the performance of AI solutions.
 </li>
 <li>
 Integrate AI outputs into analytical workflows, dashboards, reporting tools, and client delivery pipelines.
 </li>
 </ul>
 
 
 
 
 
 Full-Stack Application Development:
 
 
 <ul>
 <li>
 Design and contribute to the development of production-grade AI and data applications, primarily using Python and backend frameworks such as FastAPI.
 </li>
 <li>
 Build or support frontend interfaces using modern frameworks such as React, Next.js, or Vue to make AI and data products accessible to business users and clients.
 </li>
 <li>
 Collaborate with software engineers to define scalable application architectures, API standards, and integration patterns.
 </li>
 <li>
 Develop and maintain REST API integrations with third-party AI services, enterprise SaaS platforms, internal tools, and external data sources.
 </li>
 <li>
 Ensure that data science prototypes are translated into maintainable, secure, and scalable production solutions.
 </li>
 <li>
 Participate in code reviews, define technical best practices, and contribute to a high-quality engineering and data science culture.
 </li>
 </ul>
 
 
 
 
 
 Cloud, Deployment &amp; MLOps:
 
 
 <ul>
 <li>
 Support the containerization and cloud deployment of AI and data applications, preferably on Google Cloud Platform using GKE and Artifact Registry, while remaining adaptable to other cloud environments.
 </li>
 <li>
 Design and maintain CI/CD pipelines using GitHub Actions or equivalent tools to ensure reliable and repeatable releases.
 </li>
 <li>
 Apply MLOps and LLMOps practices to manage experimentation, deployment, monitoring, and continuous improvement of AI systems.
 </li>
 <li>
 Collaborate with engineering and infrastructure teams to ensure the reliability, scalability, and performance of production environments.
 </li>
 <li>
 Proactively identify performance bottlenecks in AI workflows, data pipelines, application layers, and infrastructure.
 </li>
 </ul>
 
 
 
 
 
 Technical Leadership &amp; Collaboration:
 
 
 <ul>
 <li>
 Lead applied AI and data science initiatives from discovery and prototyping through production deployment.
 </li>
 <li>
 Mentor junior data scientists, AI engineers, and developers on data science methods, AI integration, coding practices, and production readiness.
 </li>
 <li>
 Work closely with product teams, consultants, analysts, and non-technical stakeholders to ensure solutions are aligned with business needs.
 </li>
 <li>
 Define standards and best practices for AI solution design, evaluation, documentation, and delivery.
 </li>
 <li>
 Communicate complex technical concepts clearly to both technical and non-technical audiences.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 4 to 6 years of experience in data science, AI development, applied machine learning, or related technical roles, with hands-on experience delivering production-grade AI or data products.
 </li>
 <li>
 Strong proficiency in Python, with experience using data science, machine learning, and AI libraries and frameworks.
 </li>
 <li>
 Solid full-stack development background, including experience with backend frameworks such as FastAPI and modern frontend frameworks such as React, Next.js, or Vue.
 </li>
 <li>
 Deep understanding of LLMs, RAG architectures, generative AI workflows, and production-grade AI service integration, including tools such as OpenAI, Gemini, LangChain, or equivalent.
 </li>
 <li>
 Proven experience designing and implementing Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and enterprise data sources.
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 Experience building analytical workflows, dashboards, data pipelines, or AI-powered decision-support tools in a client delivery or enterprise context.
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 Hands-on experience with Docker and cloud deployment on at least one major cloud platform such as GCP, AWS, Azure, or equivalent.
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 Familiarity with container orchestration, artifact management, CI/CD pipelines, GitHub Actions, GitOps workflows, and branching strategies.
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 Strong understanding of LLM observability, AI evaluation, performance monitoring, and production reliability practices.
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 Demonstrated ability to lead technical initiatives, mentor junior team members, and collaborate effectively with product teams and business stakeholders.
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 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Software Engineering, Statistics, Applied Mathematics, or a related field.
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills:
 
 
 <ul>
 <li>
 Experience with agentic AI frameworks such as LangGraph or similar orchestration tools for building multi-step AI workflows.
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 Knowledge of advanced prompt engineering, vector database management, embedding model optimization, and AI evaluation techniques.
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 Experience with MLOps or LLMOps practices, including experiment tracking, model monitoring, and AI quality evaluation.
 </li>
 <li>
 Experience with Infrastructure as Code tools such as Terraform or Pulumi.
 </li>
 <li>
 Experience designing data models, analytical pipelines, or BI/dashboard solutions.
 </li>
 <li>
 Relevant certifications such as Google Cloud Professional Data Engineer, Google Cloud Professional Machine Learning Engineer, Google Cloud Professional Developer, or similar cloud and AI credentials.
 </li>
 </ul>
 
 
 
 
 
 What we offer:
 
 
 <ul>
 <li>
 A competitive compensation and benefits package.
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 The opportunity to lead AI and technology initiatives with real global impact.
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 A dynamic and supportive work environment that values leadership, innovation, and your contributions.
 </li>
 <li>
 Continuous learning and professional development opportunities to propel your career forward in AI and software engineering.
 </li>
 </ul>
 
 
 
 
 
 Application Process:
 
 
 
 Candidates are invited to submit a resume, cover letter, and any relevant portfolio or GitHub links showcasing their experience in web application development, AI integration, and cloud deployment. Shortlisted candidates will undergo a technical assessment and interview to demonstrate their skills and technical leadership capabilities.
 
 
 
 
 
 
 Infomineo: Where brilliant minds meet to shape the future of business.
 
 
 
 
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AI & Analytics - Sr. Software Engineer with AI Background - Cairo

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