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About This Role
Cloaked is a privacy startup dedicated to rebuilding consumer trust in how personal data is used. Our vision is to create an internet that serves the needs of its users, first and foremost \- with individual privacy and opt\-in at the core. Our product is a virtual “cloak” that you use as you visit any website \- Facebook, Amazon, etc. It lets you choose to share all, some, or none of your private information based on your personal preference.
About the Role
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We’re looking for a Senior Software Engineer to lead the development and strategic direction of Call Guard, our AI call screening product. Call Guard intercepts unknown callers, runs a real\-time AI conversation, and only rings users through if the call is legit \- protecting them from the spam, scam, and AI voice\-cloning wave. 50M\+ calls screened to date.
You’ll own the technical roadmap end\-to\-end: real\-time voice agent design, conversational latency, adversarial robustness against AI\-generated callers, and the cloud infrastructure underneath. Long\-term, this role grows beyond Call Guard. You’ll contribute across Cloaked’s engineering org and help shape how we build AI\-native consumer products at scale.
What will you do?
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- Lead the technical roadmap and architecture for Call Guard’s real\-time voice AI stack
- Design and build production voice agents that converse with unknown callers, classify intent, and block scams autonomously
- Optimize real\-time conversational latency end\-to\-end \- from STT, through agent reasoning, to TTS
- Build defenses against adversarial AI callers, including voice\-cloned attacks targeting our users
- Integrate and evaluate frontier models (LLMs, speech models, agent frameworks) for production use
- Own VoIP routing, telephony integration, and the cloud infrastructure that the voice agent runs on
- Collaborate with design, mobile, and product teams to ship voice experiences that feel effortless to end users
- Serve as the voice AI domain expert on the team, raising the engineering bar through code reviews, architecture discussions, and mentorship
- Help the team ship features faster and with fewer bugs by setting the technical standard for the product
- Actively leverage AI tools in day\-to\-day engineering work
- Contribute across engineering teams beyond Call Guard as the business scales
What skills and experiences will help you?
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- Strong software engineering fundamentals \- production systems, distributed systems, real\-time infrastructure
- Hands\-on experience building voice or conversational AI products in production
- Proficiency with modern voice AI stacks: STT (Whisper, Deepgram, etc.), TTS (ElevenLabs, Cartesia, etc.), real\-time orchestration (LiveKit, Pipecat, or similar)
- Deep familiarity with LLMs and agent frameworks (LangChain, LlamaIndex, LangGraph, or equivalents) in production environments
- Experience optimizing for sub\-second end\-to\-end latency in real\-time systems
- Proficiency in Python and/or Go, with a track record of building scalable backend systems
- Experience designing and deploying secure, production\-grade APIs
- Strong understanding of cloud infrastructure (AWS, GCP) and containerized deployments
- Track record shipping consumer products at scale
- Active daily use of AI coding tools (Cursor, Claude, Codex) with strong prompt judgment and tool selection instincts
What’s nice to have?
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- Experience with telephony, VoIP, SIP, or carrier\-level call routing
- Background in speech recognition, signal processing, or audio engineering
- Familiarity with adversarial ML, AI safety, or anti\-fraud system design
- PII handling and sensitive data awareness
- Prior exposure to consumer privacy or security\-focused products
- Experience with WebRTC or real\-time media infrastructure
What do we like?
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- Passion for security, privacy, and internet ethics
- Curiosity and constant learning at the frontier of voice AI and applied ML
- Strong analytical thinking with proactive problem\-solving abilities
- Ownership mentality \- comfortable holding the pen on technical direction
- Effective team player in high\-velocity environments
- Comfortable mentoring and knowledge sharing across teams
- Experience in startups or growth\-stage companies
- Interest in data tracking, analytics, and product instrumentation
What We Offer
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Cloaked is a well\-funded Series B startup based out of NYC.
Although we are a distributed team, the NYC team operates with a hybrid model. The office building is home to several amenities, including a gourmet cafe, cocktail bar, and a rooftop work area.
We have a fully built out kitchen packed with drinks and snacks. The Cloaked team has diverse interests and so we frequently embark on team outings and go out for socials!
Compensation and Benefits
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We offer above market rate pay and equity based off of the market’s best commercially available data. Your compensation will be a combination of salary, bonus and equity.
Cloaked employees have 401K, as well as top of the line Health, Dental, and Vision benefits.
We offer flexible work arrangements and the ability to work remotely as needed. Cloaked provides a home office stipend in addition to a new company laptop (and other tech depending on the role).
Perks
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Competitive PTO: We encourage employees to take a minimum \# of vacation per quarter. We see PTO as a preventative burnout measure and are committed to changing the industry standard.
Monthly health stipend: Used for any kind of physical, mental or emotional care you’d like to take for yourself, be it a gym membership, a meditation app, or time with a personal trainer.
Late Night Meals: We understand that sometimes work can get in the way of meal prep. In response to that, we offer employees a monthly meal stipend to be used when they don’t have time to get a home cooked meal going!
Professional Growth: Opportunities for career development and personal growth are provided to all employees who seek to further their knowledge and capabilities through an unlimited professional development fund. Additionally team members are encouraged to regularly attend conferences and industry events.
We are really excited about having you join our mission\-driven team and help us build the future of online privacy!
Compensation Range: $180K \- $275K
Salary Context
This $180K-$275K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $190K across 251 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At Cloaked, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 863 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $180K to $275K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Cloaked AI Hiring
Cloaked has 1 open AI role right now. They're hiring across AI Software Engineer. Based in New York, NY, US. Compensation range: $275K - $275K.
Location Context
AI roles in New York pay a median of $211,000 across 2,760 tracked positions. That's 5% above the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (1,901) and senior (1,663) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $274,200 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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